banner_dhc_mobile-05

āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ•

āļŠāļēāļ‚āļēāļ§āļīāļŠāļēāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđāļĨāļ°āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒāđƒāļ™āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļž

Master of Science Program in Digital and AI Technologies
in Health Systems (Interdisciplinary Program)

āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ—āļĩāđˆāļ­āļ­āļāđāļšāļšāļĄāļēāđ€āļžāļ·āđˆāļ­āļŠāļĢāđ‰āļēāļ‡āļœāļđāđ‰āļ™āļģāļĢāļļāđˆāļ™āđƒāļŦāļĄāđˆāļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāđ€āļŠāļĩāđˆāļĒāļ§āļŠāļēāļāļ—āļąāđ‰āļ‡āļ”āđ‰āļēāļ™āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩ AI āđāļĨāļ°āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāļ”āļīāļˆāļīāļ—āļąāļĨ āļšāļąāļ“āļ‘āļīāļ•āļ‚āļ­āļ‡āđ€āļĢāļēāļˆāļ°āļĄāļĩāļ—āļąāļāļĐāļ°āđƒāļ™āļāļēāļĢāļ™āļģāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđāļĨāļ°āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒāļĄāļēāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļāļąāļšāļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļšāļĢāļīāļāļēāļĢāļŠāļļāļ‚āļ āļēāļžāļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļž āļŠāļēāļĄāļēāļĢāļ–āļ—āļģāļ‡āļēāļ™āļĢāđˆāļ§āļĄāļāļąāļšāļ—āļĩāļĄāļŠāļŦāļŠāļēāļ‚āļēāļ§āļīāļŠāļē āđāļĨāļ°āļĢāđˆāļ§āļĄāļ‚āļąāļšāđ€āļ„āļĨāļ·āđˆāļ­āļ™ āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļ„āļĢāļąāđ‰āļ‡āļŠāļģāļ„āļąāļāļ‚āļ­āļ‡āļ āļđāļĄāļīāļ—āļąāļĻāļ™āđŒāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđƒāļŦāđ‰āļ—āļąāļ™āļŠāļĄāļąāļĒ āļŠāļ­āļ”āļ„āļĨāđ‰āļ­āļ‡āļāļąāļšāļšāļĢāļīāļšāļ—āļ‚āļ­āļ‡āđ‚āļĨāļāļĒāļļāļ„āļ”āļīāļˆāļīāļ—āļąāļĨ

āđ€āļ™āļ·āđˆāļ­āļ‡āļˆāļēāļāđ‚āļĨāļāļāļģāļĨāļąāļ‡āļāđ‰āļēāļ§āđ€āļ‚āđ‰āļēāļŠāļđāđˆāļĒāļļāļ„āļ—āļĩāđˆāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ āđāļĨāļ°āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒ āļĄāļĩāļšāļ—āļšāļēāļ—āļŠāļģāļ„āļąāļāļ•āđˆāļ­āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļŠāļļāļ‚āļ āļēāļž āļāļēāļĢāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļž āļ—āļĩāđˆāļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāđƒāļ™āļ›āļąāļˆāļˆāļļāļšāļąāļ™āļˆāļģāđ€āļ›āđ‡āļ™āļ•āđ‰āļ­āļ‡āļœāļŠāļĄāļœāļŠāļēāļ™āļ„āļ§āļēāļĄāļĢāļđāđ‰āļ”āđ‰āļēāļ™āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩ āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒāđāļĨāļ°āļāļēāļĢāļ”āļđāđāļĨāļŠāļļāļ‚āļ āļēāļžāđ€āļ‚āđ‰āļēāļ”āđ‰āļ§āļĒāļāļąāļ™ āđ€āļžāļ·āđˆāļ­āļĒāļāļĢāļ°āļ”āļąāļšāļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāđāļžāļ—āļĒāđŒāđƒāļŦāđ‰āļĄāļĩāļ„āļ§āļēāļĄāđāļĄāđˆāļ™āļĒāļģ āļĢāļ§āļ”āđ€āļĢāđ‡āļ§ āļ›āļĨāļ­āļ”āļ āļąāļĒ āđāļĨāļ°āļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļĄāļēāļāļĒāļīāđˆāļ‡āļ‚āļķāđ‰āļ™

āļ™āļīāļŠāļīāļ•āļ—āļĩāđˆāđ€āļĢāļĩāļĒāļ™āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ™āļĩāđ‰āļˆāļ°āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđāļĨāļ°āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒ āđ„āļ›āļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļšāļĢāļīāļāļēāļĢāļŠāļļāļ‚āļ āļēāļž āļ—āļĩāđˆāļ•āļ­āļšāđ‚āļˆāļ—āļĒāđŒāļ„āļ§āļēāļĄāļ•āđ‰āļ­āļ‡āļāļēāļĢāļ‚āļ­āļ‡āļœāļđāđ‰āđƒāļŠāđ‰āļ‡āļēāļ™āđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āļ•āļĢāļ‡āļˆāļļāļ” āļ­āļĩāļāļ—āļąāđ‰āļ‡āļĒāļąāļ‡āļ•āļ­āļšāļŠāļ™āļ­āļ‡āļ•āđˆāļ­āđāļ™āļ§āđ‚āļ™āđ‰āļĄāļ‚āļ­āļ‡āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄāļŠāļļāļ‚āļ āļēāļž āļ—āļĩāđˆāļāļģāļĨāļąāļ‡āđ€āļ„āļĨāļ·āđˆāļ­āļ™āđ€āļ‚āđ‰āļēāļŠāļđāđˆāļĒāļļāļ„āļ”āļīāļˆāļīāļ—āļąāļĨāļ­āļĒāđˆāļēāļ‡āļĢāļ§āļ”āđ€āļĢāđ‡āļ§

digital health

āļ„āļ“āļ°āļāļĢāļĢāļĄāļāļēāļĢāļšāļĢāļīāļŦāļēāļĢāļŦāļĨāļąāļāļŠāļđāļ•āļĢ

Program Committee

āļĢāļĻ.āļ”āļĢ.āļžāļ.āļĢāļļāđˆāļ‡āļĪāļ”āļĩ
āļŠāļąāļĒāļ˜āļĩāļĢāļāļīāļˆ

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļ„āļ“āļšāļ”āļĩ
āļāđˆāļēāļĒāļ™āļ§āļąāļ•āļāļĢāļĢāļĄāđāļ™āļ§āļšāļđāļĢāļ“āļēāļāļēāļĢ
āđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ āļ„āļ“āļ°āđāļžāļ—āļĒāļĻāļēāļŠāļ•āļĢāđŒ
āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļĢāļĻ. āļ”āļĢ.āļ­āļ•āļīāļ§āļ‡āļĻāđŒ
āļŠāļļāļŠāļēāđ‚āļ•

āļĢāļ­āļ‡āļ„āļ“āļšāļ”āļĩ āļāđˆāļēāļĒāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻ
āļ„āļ“āļ°āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļĻāļēāļŠāļ•āļĢāđŒ
āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļĢāļĻ.āļ”āļĢ.āļžāļ. āđ‚āļŠāļŽāļžāļąāļ—āļ˜āđŒ
āđ€āļŦāļĄāļĢāļąāļāļŠāđŒāđ‚āļĢāļˆāļ™āđŒ

āļĢāļ­āļ‡āļ„āļ“āļšāļ”āļĩ āļāđˆāļēāļĒāļ™āļ§āļąāļ•āļāļĢāļĢāļĄāđāļ™āļ§āļšāļđāļĢāļ“āļēāļāļēāļĢ āđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ āļ„āļ“āļ°āđāļžāļ—āļĒāļĻāļēāļŠāļ•āļĢāđŒ āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļ”āļĢ.āļ™āļž. āļžāļ‡āļĻāļ˜āļĢ
āļžāļ­āļāđ€āļžāļīāđˆāļĄāļ”āļĩ

āļ­āļ˜āļīāļšāļ”āļĩāļāļĢāļĄāļāļēāļĢāđāļžāļ—āļĒāđŒāđāļœāļ™āđ„āļ—āļĒ
āđāļĨāļ°āļāļēāļĢāđāļžāļ—āļĒāđŒāļ—āļēāļ‡āđ€āļĨāļ·āļ­āļ

āļ™āļž. āđ‚āļŠāļ āļ“ āđ€āļĄāļ†āļ˜āļ™

āļ­āļ”āļĩāļ•āļ›āļĨāļąāļ”āļāļĢāļ°āļ—āļĢāļ§āļ‡āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚

āļ”āļĢ.āļ™āļž. āļĻāļļāļ āļĪāļāļĐāđŒ
āļ–āļ§āļīāļĨāļĨāļēāļ 

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļœāļđāđ‰āļ­āđāļēāļ™āļ§āļĒāļāļēāļĢāļāļ­āļ‡āļĢāļ°āļšāļēāļ”āļ§āļīāļ—āļĒāļē
āļāļĢāļĄāļ„āļ§āļšāļ„āļļāļĄāđ‚āļĢāļ„ āļāļĢāļ°āļ—āļĢāļ§āļ‡āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚

āļĢāļĻ.āļ”āļĢ.āļ™āļž. āļŠāļąāļĒāļ āļąāļ—āļĢ
āļŠāļļāļ“āļŦāļĢāļąāļĻāļĄāļīāđŒ

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļœāļđāđ‰āļ­āđāļēāļ™āļ§āļĒāļāļēāļĢāļ”āđ‰āļēāļ™āļāļēāļĢāļšāļĢāļīāļŦāļēāļĢāđāļĨāļ°āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ āđ‚āļĢāļ‡āļžāļĒāļēāļšāļēāļĨāļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒ āļŠāļ āļēāļāļēāļŠāļēāļ”āđ„āļ—āļĒ

āļĢāļĻ.āļ”āļĢ. āđ‚āļ›āļĢāļ”āļ›āļĢāļēāļ™
āļšāļļāļ“āļĒāļžāļļāļāļāļ“āļ°

āļ­āļēāļˆāļēāļĢāļĒāđŒāļ āļēāļ„āļ§āļīāļŠāļēāļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒ āļ„āļ“āļ°āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļĻāļēāļŠāļ•āļĢāđŒ āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļ™āļž. āđ€āļŠāļĢāļīāļĄāđ€āļāļĩāļĒāļĢāļ•āļī āļŦāļĨāđˆāļ­āļĨāļąāļāļĐāļ“āđŒ

āļ­āļēāļˆāļēāļĢāļĒāđŒāļ”āđ‰āļēāļ™āļāļēāļĢāļšāļĢāļīāļŦāļēāļĢāđāļĨāļ°āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ āđ‚āļĢāļ‡āļžāļĒāļēāļšāļēāļĨāļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒ āļŠāļ āļēāļāļēāļŠāļēāļ”āđ„āļ—āļĒ

āļĢāļĻ.āļ”āļĢ. āđ€āļāļĢāļīāļ
āļ āļīāļĢāļĄāļĒāđŒāđ‚āļŠāļ āļē

āļĢāļ­āļ‡āļŦāļąāļ§āļŦāļ™āđ‰āļēāļ āļēāļ„āļ§āļīāļŠāļēāļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒ āļ„āļ“āļ°āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļĻāļēāļŠāļ•āļĢāđŒ āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļœāļĻ.āļ”āļĢ. āļŠāļīāļĢāļ°
āļĻāļĢāļĩāļŠāļ§āļąāļŠāļ”āļīāđŒ

āļŦāļąāļ§āļŦāļ™āđ‰āļēāļĻāļđāļ™āļĒāđŒ Center for AI in Medicine (CU-AIM) āļ„āļ“āļ°āđāļžāļ—āļĒāļĻāļēāļŠāļ•āļĢāđŒ āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļ­.āļ”āļĢ. āļ›āļĢāļ°āļ§āļĩāļĢāđŒ
āđ€āļ„āļĢāļ·āļ­āđ‚āļŠāļ•āļīāļāļļāļĨ

āļ­āļēāļˆāļēāļĢāļĒāđŒāļ›āļĢāļ°āļˆāļģāļ‡āļēāļ™āļ™āļ§āļąāļ•āļāļĢāļĢāļĄāđāļ™āļ§āļšāļđāļĢāļ“āļēāļāļēāļĢāđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ
āļ„āļ“āļ°āđāļžāļ—āļĒāļĻāļēāļŠāļ•āļĢāđŒ āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ

āļ™āļž. āļ§āļĻāļīāļ™ āđ€āļĨāļēāļŦāļ§āļīāļ™āļīāļˆ

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļ„āļ“āļšāļ”āļĩāļ”āđ‰āļēāļ™āđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡āļžāļ·āđ‰āļ™āļāļēāļ™āđāļĨāļ°āļĢāļ°āļšāļšāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻ

āļ”āļĢ.āļ™āļēāļĒāđāļžāļ—āļĒāđŒ āļŠāļēāļ§āļīāļ—
āļ•āļąāļ™āļ§āļĩāļĢāļ°āļŠāļąāļĒāļŠāļāļļāļĨ

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļ„āļ“āļšāļ”āļĩāļ”āđ‰āļēāļ™āļ™āļ§āļąāļ•āļāļĢāļĢāļĄāđāļ™āļ§āļšāļđāļĢāļ“āļēāļāļēāļĢāđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ

āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ™āļĩāđ‰āđ€āļŦāļĄāļēāļ°āļŠāļģāļŦāļĢāļąāļšāđƒāļ„āļĢ?

āđ€āļŦāļĄāļēāļ°āļŠāļģāļŦāļĢāļąāļšāļšāļļāļ„āļ„āļĨāļ—āļĩāđˆāļŠāļ™āđƒāļˆāđƒāļŠāđ‰āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđ€āļžāļ·āđˆāļ­āļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒ āļĢāļ§āļĄāļ–āļķāļ‡

āļšāļļāļ„āļĨāļēāļāļĢāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚

āļ—āļĩāđˆāļ•āđ‰āļ­āļ‡āļāļēāļĢāđƒāļŠāđ‰āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđ€āļžāļ·āđˆāļ­āļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļž

āļ§āļīāļĻāļ§āļāļĢ āļ™āļąāļāļžāļąāļ’āļ™āļēāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āđ‰āļēāļ™āļŠāļļāļ‚āļ āļēāļž āļ™āļąāļāļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ

āļ—āļĩāđˆāļ•āđ‰āļ­āļ‡āļāļēāļĢāļ™āļģāļ„āļ§āļēāļĄāļĢāļđāđ‰āđ„āļ›āļžāļąāļ’āļ™āļēāļ™āļ§āļąāļ•āļāļĢāļĢāļĄ āļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāđāļžāļ—āļĒāđŒ āđāļ­āļ›āļžāļĨāļīāđ€āļ„āļŠāļąāļ™āļŦāļĢāļ·āļ­āđāļžāļĨāļ•āļŸāļ­āļĢāđŒāļĄāļ”āļīāļˆāļīāļ—āļąāļĨāļŠāļģāļŦāļĢāļąāļšāļāļēāļĢāļ”āļđāđāļĨāļŠāļļāļ‚āļ āļēāļž

āļœāļđāđ‰āļ›āļĢāļ°āļāļ­āļšāļāļēāļĢāļŠāļēāļĒ HealthTech āđāļĨāļ° Startup āļ”āđ‰āļēāļ™ Digital Health

āļ—āļĩāđˆāļŠāļ™āđƒāļˆāļĨāļ‡āļ—āļļāļ™āđƒāļ™āļ˜āļļāļĢāļāļīāļˆāļ”āđ‰āļēāļ™ AI Healthcare āđāļĨāļ° Digital Wellness

Career Path

āļ™āļąāļāļ§āļīāļˆāļąāļĒāļ”āđ‰āļēāļ™āļŠāļļāļ‚āļ āļēāļžāļ”āļīāļˆāļīāļ—āļąāļĨ

(Digital Health Researcher)

āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđāļĨāļ°āļ­āļ­āļāđāļšāļšāļĢāļ°āļšāļšāļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒāļ—āļēāļ‡āļŠāļļāļ‚āļ āļēāļžāļ”āļīāļˆāļīāļ—āļąāļĨ

(Digital Health Analyst)

āļ™āļ§āļąāļ•āļāļĢāļ—āļēāļ‡āļŠāļļāļ‚āļ āļēāļžāļ”āļīāļˆāļīāļ—āļąāļĨ

(Digital Health Innovator)

āļ™āļąāļāļšāļĢāļīāļŦāļēāļĢāļĢāļ°āļšāļš āļ‚āđ‰āļ­āļĄāļđāļĨ āļ™āđ‚āļĒāļšāļēāļĒ āļ”āđ‰āļēāļ™āļŠāļļāļ‚āļ āļēāļžāļ”āļīāļˆāļīāļ—āļąāļĨ

(Digital Health Policy Administrator)

āļ™āļąāļāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒ

(AI Developer)

āļœāļđāđ‰āļˆāļąāļ”āļāļēāļĢāļāļēāļĢāļšāļĢāļīāļāļēāļĢāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļŠāļļāļ‚āļ āļēāļž

(Medical and Health Services Manager)

āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ

āļ”āđ‰āļēāļ™āļ‚āđ‰āļ­āļĄāļđāļĨāļŠāļļāļ‚āļ āļēāļž (Health Information Analysts)

āļœāļđāđ‰āļ”āļđāđāļĨāļĢāļ°āļšāļšāļāļēāļ™āļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒ

(Medical Database Administrator)

āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļĢāļ°āļšāļšāļ„āļ§āļēāļĄāļ›āļĨāļ­āļ”āļ āļąāļĒāļ‚āļ­āļ‡āļ‚āđ‰āļ­āļĄāļđāļĨāļŠāļļāļ‚āļ āļēāļž

(Health Information Security Analyst)

FAQ

1. āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļŠāļēāļ‚āļēāļ§āļīāļŠāļēāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđāļĨāļ°āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒāđƒāļ™āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāļ„āļ·āļ­āļ­āļ°āđ„āļĢ?

āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ™āļĩāđ‰āļšāļđāļĢāļ“āļēāļāļēāļĢāļ„āļ§āļēāļĄāļĢāļđāđ‰āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļŠāļļāļ‚āļ āļēāļž āļāļēāļĢāđāļžāļ—āļĒāđŒ āđāļĨāļ°āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒ āđ€āļ™āđ‰āļ™āļāļēāļĢāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āļ‚āļ­āļ‡āđ€āļ„āļĢāļ·āđˆāļ­āļ‡ (Machine Learning), āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒ (AI) āđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđƒāļ™āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāđāļžāļ—āļĒāđŒ āđ€āļžāļ·āđˆāļ­āļžāļąāļ’āļ™āļēāļāļĢāļ°āļšāļ§āļ™āļāļēāļĢāļ§āļīāļ™āļīāļˆāļ‰āļąāļĒ āļāļēāļĢāļĢāļąāļāļĐāļē āļāļēāļĢāļ”āļđāđāļĨāļœāļđāđ‰āļ›āđˆāļ§āļĒ āđāļĨāļ°āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨāļ‚āļ™āļēāļ”āđƒāļŦāļāđˆ (Big Data) āļ”āđ‰āļ§āļĒāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ—āļĩāđˆāļ—āļąāļ™āļŠāļĄāļąāļĒ āļĢāļ§āļĄāļ–āļķāļ‡āļˆāļĢāļīāļĒāļ˜āļĢāļĢāļĄāđƒāļ™āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ‚āđ‰āļ­āļĄāļđāļĨāđāļĨāļ°āļāļēāļĢāđƒāļŠāđ‰āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ

āđ€āļŦāļĄāļēāļ°āļŠāļģāļŦāļĢāļąāļšāļšāļļāļ„āļ„āļĨāļ—āļĩāđˆāļŠāļ™āđƒāļˆāđƒāļŠāđ‰ AI, āļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āļ‚āļ­āļ‡āđ€āļ„āļĢāļ·āđˆāļ­āļ‡ (Machine Learning) āđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđ€āļžāļ·āđˆāļ­āļžāļąāļ’āļ™āļēāđāļĨāļ°āļˆāļąāļ”āļāļēāļĢāļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒ āļĢāļ§āļĄāļ–āļķāļ‡: 
āļ™āļąāļāļžāļąāļ’āļ™āļēāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āđ‰āļēāļ™āļŠāļļāļ‚āļ āļēāļž āļ§āļīāļĻāļ§āļāļĢāļ‚āđ‰āļ­āļĄāļđāļĨ āļ™āļąāļāļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ āļ—āļĩāđˆāļ•āđ‰āļ­āļ‡āļāļēāļĢāļ™āļģāļ„āļ§āļēāļĄāļĢāļđāđ‰āđ„āļ›āļžāļąāļ’āļ™āļēāļ™āļ§āļąāļ•āļāļĢāļĢāļĄāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāđāļžāļ—āļĒāđŒ āļžāļąāļ’āļ™āļēāđāļ­āļ›āļžāļĨāļīāđ€āļ„āļŠāļąāļ™āļŦāļĢāļ·āļ­āđāļžāļĨāļ•āļŸāļ­āļĢāđŒāļĄāļ”āļīāļˆāļīāļ—āļąāļĨāļŠāļģāļŦāļĢāļąāļšāļāļēāļĢāļ”āļđāđāļĨāļŠāļļāļ‚āļ āļēāļž

  • āļœāļđāđ‰āļ›āļĢāļ°āļāļ­āļšāļāļēāļĢāļŠāļēāļĒ HealthTech āđāļĨāļ° Startup āļ”āđ‰āļēāļ™ Digital Health āļ—āļĩāđˆāļŠāļ™āđƒāļˆāļĨāļ‡āļ—āļļāļ™āđƒāļ™āļ˜āļļāļĢāļāļīāļˆāļ”āđ‰āļēāļ™ AI Healthcare āđāļĨāļ° Digital Wellness
  • āļšāļļāļ„āļĨāļēāļāļĢāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚āļ—āļĩāđˆāļ•āđ‰āļ­āļ‡āļāļēāļĢāđƒāļŠāđ‰āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđ€āļžāļ·āđˆāļ­āļ›āļĢāļąāļšāļ›āļĢāļļāļ‡āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāļšāļĢāļīāļŦāļēāļĢāļˆāļąāļ”āļāļēāļĢ
  • āļœāļđāđ‰āļšāļĢāļīāļŦāļēāļĢāđ‚āļĢāļ‡āļžāļĒāļēāļšāļēāļĨāđāļĨāļ°āļ­āļ‡āļ„āđŒāļāļĢāļ”āđ‰āļēāļ™āļŠāļļāļ‚āļ āļēāļžāļ—āļĩāđˆāļ•āđ‰āļ­āļ‡āļāļēāļĢāļ™āļģāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđāļĨāļ°āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒ āđ„āļ”āđ‰āđāļāđˆ Big Data, Telemedicine, IoT, Wearable Device āđ€āļ›āđ‡āļ™āļ•āđ‰āļ™ āļĄāļēāđƒāļŠāđ‰āđ€āļžāļ·āđˆāļ­āđ€āļžāļīāđˆāļĄāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāļ‚āļ­āļ‡āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļž
  • āļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļ—āļĩāđˆāļĒāļ·āļ”āļŦāļĒāļļāđˆāļ™āđāļĨāļ°āđ€āļĢāđˆāļ‡āļĢāļąāļ”: āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ–āļđāļāļ­āļ­āļāđāļšāļšāđƒāļŦāđ‰āđ€āļŦāļĄāļēāļ°āļāļąāļšāļšāļļāļ„āļĨāļēāļāļĢāļ—āļĩāđˆāļ—āļģāļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ āđ‚āļ”āļĒāđƒāļŠāđ‰ āļĢāļđāļ›āđāļšāļšāļāļēāļĢāđ€āļĢāļĩāļĒāļ™āđāļšāļš Hybrid (āļ­āļ­āļ™āđ„āļĨāļ™āđŒ + āļ­āļ­āļ™āđ„āļ‹āļ•āđŒ) āļ‹āļķāđˆāļ‡āļŠāđˆāļ§āļĒāđƒāļŦāđ‰āļ™āļīāļŠāļīāļ•āļŠāļēāļĄāļēāļĢāļ–āđ€āļĢāļĩāļĒāļ™āļ„āļ§āļšāļ„āļđāđˆāđ„āļ›āļāļąāļšāļāļēāļĢāļ—āļģāļ‡āļēāļ™āđ„āļ”āđ‰ āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļ–āļŠāļģāđ€āļĢāđ‡āļˆāļāļēāļĢāļĻāļķāļāļĐāļēāđ„āļ”āđ‰āđ€āļĢāđ‡āļ§āļ—āļĩāđˆāļŠāļļāļ”āļ āļēāļĒāđƒāļ™ 1 āļ›āļĩāļāļēāļĢāļĻāļķāļāļĐāļē
  • āļāļēāļĢāļšāļđāļĢāļ“āļēāļāļēāļĢāļĻāļēāļŠāļ•āļĢāđŒāļ—āļĩāđˆāļŦāļĨāļēāļāļŦāļĨāļēāļĒ: āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ™āļĩāđ‰āđ€āļ›āđ‡āļ™āļŦāļ™āļķāđˆāļ‡āđƒāļ™āđ„āļĄāđˆāļāļĩāđˆāļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ—āļĩāđˆāđ€āļŠāļ·āđˆāļ­āļĄāđ‚āļĒāļ‡āļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļŠāļļāļ‚āļ āļēāļž āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļĻāļēāļŠāļ•āļĢāđŒ āđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨāđ€āļ‚āđ‰āļēāļ”āđ‰āļ§āļĒāļāļąāļ™ āļ—āļģāđƒāļŦāđ‰āđ€āļāļīāļ”āļ­āļ‡āļ„āđŒāļ„āļ§āļēāļĄāļĢāļđāđ‰āļ—āļĩāđˆāļŠāļĄāļ”āļļāļĨāđāļĨāļ°āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ„āļ›āđƒāļŠāđ‰āđ„āļ”āđ‰āļˆāļĢāļīāļ‡āđƒāļ™āļ āļēāļ„āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄāļŠāļļāļ‚āļ āļēāļž
  • Co-Creation āļāļąāļšāļœāļđāđ‰āđƒāļŠāđ‰āļˆāļĢāļīāļ‡: āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ™āļĩāđ‰āļ­āļ­āļāđāļšāļšāđ‚āļ”āļĒ āļ„āļ§āļēāļĄāļĢāđˆāļ§āļĄāļĄāļ·āļ­āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ­āļēāļˆāļēāļĢāļĒāđŒ āļ™āļąāļāļ§āļīāļˆāļąāļĒ āđāļžāļ—āļĒāđŒ āļ§āļīāļĻāļ§āļāļĢ āđāļĨāļ°āļ­āļ‡āļ„āđŒāļāļĢāļœāļđāđ‰āđƒāļŠāđ‰āļšāļąāļ“āļ‘āļīāļ• āđ€āļŠāđˆāļ™ āļāļĢāļ°āļ—āļĢāļ§āļ‡āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚ āđ‚āļĢāļ‡āļžāļĒāļēāļšāļēāļĨ āđāļĨāļ°āļ āļēāļ„āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄ HealthTech āļ—āļģāđƒāļŦāđ‰āđāļ™āđˆāđƒāļˆāđ„āļ”āđ‰āļ§āđˆāļēāļ­āļ‡āļ„āđŒāļ„āļ§āļēāļĄāļĢāļđāđ‰āļ—āļĩāđˆāļŠāļ­āļ™āļŠāļēāļĄāļēāļĢāļ–āļ•āļ­āļšāđ‚āļˆāļ—āļĒāđŒāļ„āļ§āļēāļĄāļ•āđ‰āļ­āļ‡āļāļēāļĢāļ‚āļ­āļ‡āļ•āļĨāļēāļ”āļ‡āļēāļ™āđāļĨāļ°āļ āļēāļ„āļāļēāļĢāđāļžāļ—āļĒāđŒāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđāļ—āđ‰āļˆāļĢāļīāļ‡
  • āļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āļ—āļĩāđˆāđ€āļ™āđ‰āļ™āļāļēāļĢāļĨāļ‡āļĄāļ·āļ­āļ—āļģ (Project-Based Learning): āļ™āļīāļŠāļīāļ•āļˆāļ°āđ„āļ”āđ‰āļ—āļģāļ‡āļēāļ™āđāļĨāļ°āļžāļąāļ’āļ™āļēāđ‚āļ„āļĢāļ‡āļāļēāļĢāļˆāļĢāļīāļ‡ (Capstone Project) āļĢāđˆāļ§āļĄāļāļąāļšāļ­āļ‡āļ„āđŒāļāļĢāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļšāļĢāļīāļĐāļąāļ—āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩ āđ‚āļ”āļĒāļĄāļĩāļ­āļēāļˆāļēāļĢāļĒāđŒāļ—āļĩāđˆāļ›āļĢāļķāļāļĐāļēāļˆāļēāļāļ—āļąāđ‰āļ‡āļ āļēāļ„āļ§āļīāļŠāļēāļāļēāļĢāđāļĨāļ°āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄāļ„āļ­āļĒāļ”āļđāđāļĨāļ­āļĒāđˆāļēāļ‡āđƒāļāļĨāđ‰āļŠāļīāļ”
  • āđ€āļ„āļĢāļ·āļ­āļ‚āđˆāļēāļĒāđāļĨāļ°āđ‚āļ­āļāļēāļŠāđƒāļ™āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄ: āļ™āļīāļŠāļīāļ•āļˆāļ°āđ„āļ”āđ‰āđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰ āļĢāļąāļšāđāļ™āļ§āļ„āļīāļ” āļĻāļķāļāļĐāļēāļ”āļđāļ‡āļēāļ™āđƒāļ™āļšāļĢāļīāļĐāļąāļ— HealthTech āļŠāļąāđ‰āļ™āļ™āļģ āđ‚āļĢāļ‡āļžāļĒāļēāļšāļēāļĨ āđāļĨāļ°āļŠāļ–āļēāļšāļąāļ™āļ§āļīāļˆāļąāļĒāļĢāļ°āļ”āļąāļšāļŠāļēāļ•āļī

āļ™āļīāļŠāļīāļ•āļˆāļ°āļŠāļģāđ€āļĢāđ‡āļˆāļāļēāļĢāļĻāļķāļāļĐāļēāđ€āļĄāļ·āđˆāļ­āļœāđˆāļēāļ™āđ€āļāļ“āļ‘āđŒāļ—āļļāļāļ‚āđ‰āļ­āļ”āļąāļ‡āļ™āļĩāđ‰

  • āļĻāļķāļāļĐāļēāļĢāļēāļĒāļ§āļīāļŠāļēāļ„āļĢāļšāļ–āđ‰āļ§āļ™āļ•āļēāļĄāļ—āļĩāđˆāļāļģāļŦāļ™āļ”āđƒāļ™āļŦāļĨāļąāļāļŠāļđāļ•āļĢāđ‚āļ”āļĒāđ„āļ”āđ‰āļœāļĨāļ›āļĢāļ°āđ€āļĄāļīāļ™āđ€āļ›āđ‡āļ™ S āļ—āļļāļāļĢāļēāļĒāļ§āļīāļŠāļē
  • āļ™āļģāđ€āļŠāļ™āļ­āļĢāļēāļĒāļ‡āļēāļ™āļāļēāļĢāļĻāļķāļāļĐāļēāļ„āđ‰āļ™āļ„āļ§āđ‰āļēāļ­āļīāļŠāļĢāļ°āđāļĨāļ°āļŠāļ­āļšāļœāđˆāļēāļ™āļāļēāļĢāļŠāļ­āļšāļ›āļĢāļ°āļĄāļ§āļĨāļ„āļ§āļēāļĄāļĢāļđāđ‰āđāļšāļšāļ›āļēāļāđ€āļ›āļĨāđˆāļēāļ‚āļąāđ‰āļ™āļŠāļļāļ”āļ—āđ‰āļēāļĒ
  • āļ™āļģāđ€āļŠāļ™āļ­āļœāļĨāļ‡āļēāļ™āļŦāļĢāļ·āļ­āļ›āļĢāļ°āļāļ§āļ”āļ™āļ§āļąāļ•āļāļĢāļĢāļĄāđƒāļ™āđ€āļ§āļ—āļĩāļĢāļ°āļ”āļąāļšāļŠāļēāļ•āļīāļŦāļĢāļ·āļ­āļ™āļēāļ™āļēāļŠāļēāļ•āļī

āđ„āļĄāđˆāļˆāļģāđ€āļ›āđ‡āļ™ āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļ™āļĩāđ‰āđ„āļ”āđ‰āļĢāļąāļšāļāļēāļĢāļ­āļ­āļāđāļšāļšāļĄāļēāđ€āļžāļ·āđˆāļ­āđƒāļŦāđ‰āđ€āļŦāļĄāļēāļ°āļŠāļĄāļāļąāļšāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āļˆāļēāļāļŦāļĨāļēāļāļŦāļĨāļēāļĒāļŠāļēāļ‚āļē āđ‚āļ”āļĒāļĄāļļāđˆāļ‡āđ€āļ™āđ‰āļ™āļāļēāļĢāļžāļąāļ’āļ™āļēāđāļĨāļ°āļ•āđˆāļ­āļĒāļ­āļ”āļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āļ‚āļ­āļ‡āļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāļŠāļ™āđƒāļˆāļ”āđ‰āļēāļ™āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŠāļļāļ‚āļ āļēāļž āđāļĄāđ‰āļ§āđˆāļēāļˆāļ°āđ„āļĄāđˆāļĄāļĩāļžāļ·āđ‰āļ™āļāļēāļ™āļ”āđ‰āļēāļ™āļāļēāļĢāđāļžāļ—āļĒāđŒāļŦāļĢāļ·āļ­ AI āļĄāļēāļāđˆāļ­āļ™āļāđ‡āļŠāļēāļĄāļēāļĢāļ–āđ€āļ‚āđ‰āļēāļĻāļķāļāļĐāļēāđ„āļ”āđ‰ āļ‚āļ­āđ€āļžāļĩāļĒāļ‡āļ™āļīāļŠāļīāļ•āđ€āļ›āđ‡āļ™āļ™āļąāļāļ„āļīāļ”āđāļĨāļ°āļ™āļąāļāļžāļąāļ’āļ™āļēāļ—āļĩāđˆāļžāļĢāđ‰āļ­āļĄāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āđāļĨāļ°āļŠāļĢāđ‰āļēāļ‡āļŠāļĢāļĢāļ„āđŒāļ™āļ§āļąāļ•āļāļĢāļĢāļĄāđ€āļžāļ·āđˆāļ­āļ­āļ™āļēāļ„āļ•āļ‚āļ­āļ‡āļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļž

  • āļŠāļģāļŦāļĢāļąāļšāļœāļđāđ‰āļ—āļĩāđˆāļĄāļēāļˆāļēāļāļŠāļēāļĒāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩ → āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļˆāļ°āđ€āļžāļīāđˆāļĄāļāļēāļĢāđƒāļŦāđ‰āļ„āļ§āļēāļĄāļĢāļđāđ‰āļžāļ·āđ‰āļ™āļāļēāļ™āļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļĢāļ°āļšāļšāļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚ āđ€āļžāļ·āđˆāļ­āđƒāļŦāđ‰āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāđ„āļ›āļžāļąāļ’āļ™āļēāļ™āļ§āļąāļ•āļāļĢāļĢāļĄāļ—āļĩāđˆāļ•āļ­āļšāđ‚āļˆāļ—āļĒāđŒāļāļēāļĢāļ”āļđāđāļĨāļŠāļļāļ‚āļ āļēāļžāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļŦāļĄāļēāļ°āļŠāļĄ
  • āļŠāļģāļŦāļĢāļąāļšāļœāļđāđ‰āļ—āļĩāđˆāļĄāļēāļˆāļēāļāļŠāļēāļĒāļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļŠāļļāļ‚āļ āļēāļž â†’ āļŦāļĨāļąāļāļŠāļđāļ•āļĢāļˆāļ°āđ€āļžāļīāđˆāļĄāļāļēāļĢāđƒāļŦāđ‰āļ„āļ§āļēāļĄāļĢāļđāđ‰āļžāļ·āđ‰āļ™āļāļēāļ™āļ”āđ‰āļēāļ™āļ›āļąāļāļāļēāļ›āļĢāļ°āļ”āļīāļĐāļāđŒ (AI), āļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ (Data Science) āđāļĨāļ°āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ”āļīāļˆāļīāļ—āļąāļĨ āđ€āļžāļ·āđˆāļ­āļŠāđˆāļ§āļĒāđƒāļŦāđ‰āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļĄāļēāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđāļĨāļ°āļšāļĢāļīāļŦāļēāļĢāļˆāļąāļ”āļāļēāļĢāļĢāļ°āļšāļšāļŠāļļāļ‚āļ āļēāļžāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļž

Assoc. Prof. Roongruedee Chaiteerakij, M.D., Ph.D.

āļĢāļ­āļ‡āļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ.āđāļžāļ—āļĒāđŒāļŦāļāļīāļ‡ āļĢāļļāđˆāļ‡āļĪāļ”āļĩ āļŠāļąāļĒāļ˜āļĩāļĢāļāļīāļˆ

Education

â€Ē Ph.D. (Clinical and Translational Science) Mayo Clinic School of Graduate Medical Education, Rochester, MN, 2558
â€Ē Master Program (Clinical and Translational Science) Mayo Clinic School of Graduate Medical Education, Rochester, MN, 2555
â€Ē Certificate Program (Clinical and Translational Science) Mayo Clinic School of Graduate Medical Education, Rochester, MN, 2554
â€Ē M.Sc. (Medicine) Chulalongkorn University, 2551
â€Ē āļ§āļ§. (āļ­āļēāļĒāļļāļĢāļĻāļēāļŠāļ•āļĢāđŒāđ‚āļĢāļ„āļĢāļ°āļšāļšāļ—āļēāļ‡āđ€āļ”āļīāļ™āļ­āļēāļŦāļēāļĢ) āđāļžāļ—āļĒāļŠāļ āļē, 2551
â€Ē āļ§āļ§. (āļ­āļēāļĒāļļāļĢāļĻāļēāļŠāļ•āļĢāđŒ) āđāļžāļ—āļĒāļŠāļ āļē, 2549
â€Ē āļž.āļš. āđ€āļāļĩāļĒāļĢāļ•āļīāļ™āļīāļĒāļĄāļ­āļąāļ™āļ”āļąāļš 1 āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2543

Research Interest

â€Ē Liver and bile duct cancers
â€Ē AI in mecal images
â€Ē Clinical biomarkers

Publication

1. Kuaaroon W, Tiyarattanachai T, Apiparakoon T, Marukatat S, Tanpowpong N, Treeprasertsuk S, Rerknimitr R, Tangkijvanich P, Ananchuensook P, Chotiyaputta W, Samaithongcharoen K, Chaiteerakij R. Machine learning models for predicting hepatocellular carcinoma development in patients with chronic viral hepatitis B infection. Asian Biomed (Res Rev News). 2025 Feb 28;19(1):51-59. doi: 10.2478/abm-2025-0007. eCollection 2025 Feb.

2. Chaiteerakij R, Ariyaskul D, Kulkraisri K, Apiparakoon T, Sukcharoen S, Chaichuen O, Pensuwan P, Tiyarattanachai T, Rerknimitr R, Marukatat S. Artificial intelligence for ultrasonographic detection and diagnosis of hepatocellular carcinoma and cholangiocarcinoma. Sci Rep. 2024 Sep 4;14(1):20617. doi: 10.1038/s41598-024-71657-z

3. Tiyarattanachai T, Apiparakoon T, Chaichuen O, Sukcharoen S, Yimsawad S, Jangsirikul S, Chaikajornwat J, Siriwong N, Burana C, Siritaweechai N, Atipas K, Assawamasbunlue N, Tovichayathamrong P, Obcheuythed P, Somvanapanich P, Geratikornsupuk N, Anukulkarnkusol N, Sarakul P, Tanpowpong N, Pinjaroen N, Kerr SJ, Rerknimitr R, Marukatat S, Chaiteerakij R. Artificial intelligence assists operators in real-time detection of focal liver lesions during ultrasound: A randomized controlled study. Eur J Radiol. 2023 Aug;165:110932. doi: 10.1016/j.ejrad.2023.110932. Epub 2023 Jun 20.

Assoc. Prof. Atiwong Suchato, Ph.D.

āļĢāļ­āļ‡āļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ.āļ­āļ•āļīāļ§āļ‡āļĻāđŒ āļŠāļļāļŠāļēāđ‚āļ•

Education

â€Ē Ph.D. (Electrical Engineering and Computer Science) Massachusetts Institute of Technology, Cambride, MA, 2547
â€Ē S.M. (Electrical Engineering and Computer Science) Massachusetts Institute of Technology, Cambride, MA, 2543
â€Ē āļ§āļĻ.āļš. (āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāđ„āļŸāļŸāđ‰āļē) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2541 

Research Interest

â€Ē Artificial intelligence
â€Ē Machine learning
â€Ē Speech and signal processing for healthcare

Publication

1. Huangsuwan K, N Cooharojananone N, Punyabukkana P, Suchato A, et al. Enhancing Learner Engagement in Chulalongkorn University MOOC Computing Courses: Insights from Behavioral Trends and Analyses of Multiple Large Language Models. International Conference on Innovative Technologies and Learning (July 2025), 403-411.

2. Chomphooyod P, Suchato A, Tuaycharoen A, Punyabukkana P. English grammar multiple-choice question generation using Text-to-Text Transfer Transformer. Computers and Education: Artificial Intelligence (January 2023), 5, 100158.

3. Vorapatratorn S, Suchato A, Punyabukkana P. Fast obstacle detection system for the blind using depth image and machine learning. Engineering and Applied Science Research (July 2021), 48(5), 593-603.

Assoc. Prof. Solaphat Hemrungrojn, M.D., Ph.D.

āļĢāļ­āļ‡āļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ.āđāļžāļ—āļĒāđŒāļŦāļāļīāļ‡
āđ‚āļŠāļŽāļžāļąāļ—āļ˜āđŒ āđ€āļŦāļĄāļĢāļąāļāļŠāđŒāđ‚āļĢāļˆāļ™āđŒ

Education

â€Ē āļ§āļ—.āļ”. (āļāļēāļĢāļ§āļīāļˆāļąāļĒāļŠāļļāļ‚āļ āļēāļžāđāļĨāļ°āļāļēāļĢāļˆāļąāļ”āļāļēāļĢ) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2567
â€Ē Clinical Fellowship (Dementia: Alzheimer’s disease center) University of California, UCLA, 2547
â€Ē Research Fellowship (Psychiatry) Yale University, Connecticut, 2548
â€Ē āļ­āļ§. (āļˆāļīāļ•āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒāļœāļđāđ‰āļŠāļđāļ‡āļ­āļēāļĒāļļ) āđāļžāļ—āļĒāļŠāļ āļē, 2562
â€Ē āļ§āļ§. (āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒāļ„āļĢāļ­āļšāļ„āļĢāļąāļ§) āđāļžāļ—āļĒāļŠāļ āļē, 2545
â€Ē āļ§āļ§. (āļˆāļīāļ•āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒ) āđāļžāļ—āļĒāļŠāļ āļē, 2544
â€Ē āļ›.āļšāļąāļ“āļ‘āļīāļ• (āļˆāļīāļ•āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒ) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2542
â€Ē āļž.āļš. āđ€āļāļĩāļĒāļĢāļ•āļīāļ™āļīāļĒāļĄāļ­āļąāļ™āļ”āļąāļš 2 āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2541

Research Interest

â€Ē Artificial intelligence in neuroscience
â€Ē Alzheimer’s disease
â€Ē Neuropsychological assessmen

Publication

1. Hiransuthikul A, Taweephol T, Timachai N, Suksawek S, Wongvoranet C, Hemrungrojn S, et al. The Validity of Computerized Montreal Cognitive Assessment among Aging People Living with HIV. Alzheimer’s & Dementia (December 2025), 21, e107653.

2. Hiransuthikul A, Taweephol T, Timachai N, Suksawek S, Wongvoranet C, Hemrungrojn S, et al. The validity of computerized Montreal cognitive assessment among aging people living with HIV: A pilot study. BMC neurology (October 2025), 25(1), 406.

3. Pongraweewan P, Tornsatitkul S, Siriussawakul A, Krishnamoorthy V, Hiransuthikul A, Hemrungrojn S, et al. Incidence of postoperative cognitive dysfunction in older adults: a prospective cohort study using a web-based Montreal cognitive assessment application. Scientific Reports (August 2025), 15(1), 31180.

Pongsathorn Pokpermdee, M.D., Ph.D.

āļ”āļĢ.āļ™āļēāļĒāđāļžāļ—āļĒāđŒ āļžāļ‡āļĻāļ˜āļĢ āļžāļ­āļāđ€āļžāļīāđˆāļĄāļ”āļĩ

Education

â€Ē Ph.D. (Public Health & Policy) London School of Hygiene and Tropical Medicine, University of London, UK, 2548
â€Ē M.Sc. (Health Economics) University of York, UK, 2543
â€Ē Breakthrough Program for Senior Executives Institute for Management Development, 2567
â€Ē Senior Executive Fellow Harvard Kennedy School, USA, 2560
â€Ē Advanced Management Program (AMP) Havard Business School, USA, 2556
â€Ē āļ›āļĢāļ°āļāļēāļĻāļ™āļĩāļĒāļšāļąāļ•āļĢāļŦāļĨāļąāļāļŠāļđāļ•āļĢāļāļēāļĢāļāļķāļāļ­āļšāļĢāļĄ āļŠāļēāļ‚āļēāļĢāļ°āļšāļēāļ”āļ§āļīāļ—āļĒāļē (FETP) āļāļĢāļ°āļ—āļĢāļ§āļ‡āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚, 2541
â€Ē āļž.āļš. āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2535

Research Interest

â€Ē Health policy
â€Ē Health economics
â€Ē Digital health for ageing society

Publication

1. Pokpermdee P., Sukpatthanakul K., Phimla S., Pensuriya W., Charoensuntisuk N., Kongsueb P., et al. Assessment of Thailand’s health system performance in 2022-2023. Journal of Health Systems Research 2024;18(3):291-313.

2. Pokpermdee P., Phooseemungkun K., Comparative analysis on management and health benefit package between people with citizenship problem scheme and universal coverage scheme in Thailand 2020. Journal of Health Systems Research 2021;15(1):36-48.

3. Pokpermdee P., Phooseemungkun K., Comparative management and benefit packages between social security scheme and universal coverage scheme in 2020. Journal of Health Systems Research 2020;14(1):26-42.

Sopon Mekthon, M.D.

āļ™āļēāļĒāđāļžāļ—āļĒāđŒ āđ‚āļŠāļ āļ“ āđ€āļĄāļ†āļ˜āļ™

Education

â€Ē āļĢāļ›.āļĄ. āļŠāļ–āļēāļšāļąāļ™āļšāļąāļ“āļ‘āļīāļ•āļžāļąāļ’āļ™āļēāļšāļĢāļīāļŦāļēāļĢāļĻāļēāļŠāļ•āļĢāđŒ (āļ™āļīāļ”āđ‰āļē) 2545
â€Ē āļŠ.āļš. āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļŠāļļāđ‚āļ‚āļ—āļąāļĒāļ˜āļĢāļĢāļĄāļ˜āļīāļĢāļēāļŠ, 2538
â€Ē āļž.āļš. āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2523

Research Interest

â€Ē National eHealth strategy
â€Ē Health system leadership
â€Ē Digital transformation

Publication

1. Mekthon, S. (Ed.). (2016). Guidelines for Family Care Team Operation for Service Units. Nonthaburi: Agricultural Co-operative Federation of Thailand.

2. Karbwang, J., Na Bangchang, K., Thanavibul, A., Back, D. J., Bunnag, D., & Mekthon, S. (1991). Pharmacokinetics of mefloquine in the presence of primaquine. European Journal of Clinical Pharmacology, 40(3), 309–311.

3. Davis, T. M., Supanaranond, W., Pukrittayakamee, S., Karbwang, J., Molunto, P., Mekthon, S., & White, N. J. (1990). A safe and effective consecutive-infusion regimen for rapid quinine loading in severe falciparum malaria. The Journal of Infectious Diseases, 161(6), 1305–1308.

Supharerk Thawillarp, M.D., Ph.D.

āļ”āļĢ.āļ™āļēāļĒāđāļžāļ—āļĒāđŒ āļĻāļļāļ āļĪāļāļĐāđŒ āļ–āļ§āļīāļĨāļĨāļēāļ 

Education

â€Ē Dr.P.H (Public Health Informatic) Johns Hopkins University
â€Ē M.Sc. (Health Sciences Informatics) Johns Hopkins University 
â€Ē āļ§āļ§.(āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒāļ›āđ‰āļ­āļ‡āļāļąāļ™) āļāļĢāļ°āļ—āļĢāļ§āļ‡āļŠāļēāļ˜āļēāļĢāļ“āļŠāļļāļ‚
â€Ē āļž.āļš. āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļŠāļ‡āļ‚āļĨāļēāļ™āļ„āļĢāļīāļ™āļ—āļĢāđŒ

 

 

Research Interest

â€Ē Public health informatics
â€Ē Digital surveillance
â€Ē Epidemic intelligence systems

Publication

1. S Thawillarp. Comparison of Data and Performance Indicators: Before and After the Transition of Thailand’s National Disease Surveillance System, 2023–2024. Outbreak, Surveillance, Investigation & Response (OSIR) Journal (June 2025), 18 (2), 70-77.

2. āļĻāļļāļ āļĪāļāļĐāđŒ āļ–āļ§āļīāļĨāļĨāļēāļ . āļāļēāļĢāđ€āļŠāļ·āđˆāļ­āļĄāļ•āđˆāļ­āļĢāļ°āļšāļšāđƒāļšāļĢāļąāļšāļĢāļ­āļ‡āļ§āļąāļ„āļ‹āļĩāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđ„āļ›āļĒāļąāļ‡āļĢāļ°āļšāļšāđƒāļšāļĢāļąāļšāļĢāļ­āļ‡āļ§āļąāļ„āļ‹āļĩāļ™āļ”āļīāļˆāļīāļ—āļąāļĨ COVID-19 āđāļŦāđˆāļ‡āļŠāļŦāļ āļēāļžāļĒāļļāđ‚āļĢāļ›āđ€āļžāļ·āđˆāļ­āļāļēāļĢāđ€āļ”āļīāļ™āļ—āļēāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĢāļ°āđ€āļ—āļĻ
āļĢāļēāļĒāļ‡āļēāļ™āļāļēāļĢāđ€āļāđ‰āļēāļĢāļ°āļ§āļąāļ‡āļ—āļēāļ‡āļĢāļ°āļšāļēāļ”āļ§āļīāļ—āļĒāļēāļ›āļĢāļ°āļˆāļģāļŠāļąāļ›āļ”āļēāļŦāđŒ (āļĄāļīāļ–āļļāļ™āļēāļĒāļ™ 2568), (6), e5327-e5327.

3. Tanomkiat W, Chaichulee S, Ingviya T, Thawillarp S. Thailand is implementing artificial intelligence to assist interpreting chest radiographs in public health. The ASEAN Journal of Radiology (October 2025), 26(3), 270-283.

Assoc. Prof. Chaipat Chunharas, M.D., Ph.D.

āļĢāļ­āļ‡āļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ(āļžāļīāđ€āļĻāļĐ)
āļ”āļĢ. āļ™āļēāļĒāđāļžāļ—āļĒāđŒāļŠāļąāļĒāļ āļąāļ—āļĢ āļŠāļļāļ“āļŦāļĢāļąāļĻāļĄāļīāđŒ

Education

â€Ē Ph.D. (Experimental Psychology) University of California San Diego, La Jolla, CA, 2562
â€Ē Postdoctoral Fellow (Multimodal Imaging Laboratory) University of California San Diego, La Jolla, CA, 2556
â€Ē M.Sc. (Psychology) University of California San Diego, La Jolla, CA, 2558
â€Ē M.Sc. (Medicine) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2553
â€Ē āļ§āļ§. (āļ›āļĢāļ°āļŠāļēāļ—āļ§āļīāļ—āļĒāļē) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2554
â€Ē āļ§āļ§. (āļ­āļēāļĒāļļāļĢāļĻāļēāļŠāļ•āļĢāđŒ) āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļ‚āļ­āļ™āđāļāđˆāļ™, 2551
â€Ē āļž.āļš. āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2547

Research Interest

â€Ē Cognitive neuroscience
â€Ē Clinical neurology
â€Ē Computational brain research

Publication

1. Raksasat R, Teerapittayanon S, Itthipuripat S, Praditpornsilpa K, Petchlorlian A, Chotibut T, Chunharas C, Chatnuntawech I. Attentive pairwise interaction network for AI-assisted clock drawing test assessment of early visuospatial deficits. Scientific Reports. 2023 Oct 23;13(1):18113.ISSN 2045-2322 (online)

2. Kantithammakorn P, Punyabukkana P, Pratanwanich PN, Hemrungrojn S, Chunharas C, Wanvarie D. Using Automatic Speech Recognition to Assess Thai Speech Language Fluency in the Montreal Cognitive Assessment (MoCA). Sensors (Basel). 2022 Feb 17;22(4) PubMed Central PMCID: PMC8875410.

3. Metarugcheep S, Punyabukkana P, Wanvarie D, Hemrungrojn S, Chunharas C, Pratanwanich PN. Selecting the Most Important Features for Predicting Mild Cognitive Impairment from Thai Verbal Fluency Assessments. Sensors (Basel). 2022 Aug 3;22(15) PubMed PMID: 35957370.

Assoc. Prof. Proadpran Punyabukkana, Ph.D.

āļĢāļ­āļ‡āļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ.āđ‚āļ›āļĢāļ”āļ›āļĢāļēāļ™ āļšāļļāļ“āļĒāļžāļļāļāļāļ“āļ°

Education

â€Ē Ph.D. (Information Science), Claremont Graduate University, USA, 2546
â€Ē M.S. (Information Science), Claremont Graduate University, USA, 2542
â€Ē M.S. (Management Information Systems), Boston University, USA, 2532
â€Ē B.A. (Systems Analysis) University of Findlay, Ohio, 2531

Research Interest

â€Ē Assistive technology
â€Ē Speech technology
â€Ē Artificial intelligence for health

Publication

1. Thirapanish W, Kantavat P, Wanvarie D, Chuangsuwanich E, Punyabukkana P, et al. Enhancing Parkinson’s Diagnosis with PhonatoryVoice Analysis: Optimizing Machine LearningFeature Selection for Support Vector Machines. Research Square (December 2025).

2. Chakamanont S, Punyabukkana P, Sittipunt P, Wongvises K, Samoh A, Khabuan S. Advancing ChatGPT in Higher Education: Beyond Automation in Teaching Practices.
AsTEN Journal of Teacher Education (November 2025).

3. Sapsitthikul T, Pongpirul K, Kanjanabuch T, Chuengsaman P, Punyabukkana P, et al. Optimizing home visits through machine learning for preventing peritoneal dialysis-associated peritonitis: a proof of concept study and results from PDOPPS. Clinical Kidney Journal (June 2024), 17(6), sfae136.

Sermkiat Lolak, M.D., Ph.D.

āļ”āļĢ.āļ™āļēāļĒāđāļžāļ—āļĒāđŒāđ€āļŠāļĢāļīāļĄāđ€āļāļĩāļĒāļĢāļ•āļī āļŦāļĨāđˆāļ­āļĨāļąāļāļĐāļ“āđŒ

Education

â€Ē āļ§āļ—.āļ”. (āļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ”āļđāđāļĨāļŠāļļāļ‚āļ āļēāļž) āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĄāļŦāļīāļ”āļĨ, 2567
â€Ē āļ§āļ§. (āļ›āļĢāļ°āļŠāļēāļ—āļĻāļąāļĨāļĒāļĻāļēāļŠāļ•āļĢāđŒ), āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2554
â€Ē āļ›.āļšāļąāļ“āļ‘āļīāļ• āļ‚āļąāđ‰āļ™āļŠāļđāļ‡ (āļ›āļĢāļ°āļŠāļēāļ—āļĻāļąāļĨāļĒāļĻāļēāļŠāļ•āļĢāđŒ), āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2552
â€Ē āļž.āļš. āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2546

Research Interest

â€Ē Causality , Real World Evidence
â€Ē Machine learning for clinical
â€Ē risk prediction

Publication

1. Lolak S, Attia J, McKay G. J, Thakkinstian A. Application of dragonnet and conformal inference for estimating individualized treatment effects for personalized stroke prevention: Retrospective cohort study. JMIR cardio (January 2025), 9, e50627
2. Lolak S, Suppasilp C, Poprom N, Sapankaew T, Yin M. S, et al. Machine Learning Prediction of Stroke Occurrence: A Systematic Review. medRxiv (March 2024), 28, 24305014.
3. Lolak S, Attia J, McKay G. J, Thakkinstian A. Comparing explainable machine learning approaches with traditional statistical methods for evaluating stroke risk models: retrospective cohort study. JMIR cardio (July 2023), 7, e47736.

Assoc. Prof. Krerk Piromsopa, Ph.D.

āļĢāļ­āļ‡āļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ.āđ€āļāļĢāļīāļ āļ āļīāļĢāļĄāļĒāđŒāđ‚āļŠāļ āļē

Education

â€Ē Ph.D. (Computer Science), Michigan State U., USA, 2549
â€Ē āļ§āļĻ.āļĄ. (āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒ), āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2543
â€Ē āļ§āļĻ.āļš. (āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒ), āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2541

Research Interest

â€Ē Computer systems
â€Ē Cybersecurity
â€Ē Software and web-based applications

Publication

1. Phuthong T, Anuntavoranich P, Chandrachai A, Piromsopa K. Causal Modelling of the Key Competitiveness Assessment Factors of Wellness Tourism Destinations: A DEMATEL Approach. Journal of Human, Earth, and Future (June 2023), 4(2), 121-152.

2. Phuthong T, Anuntavoranich P, Chandrachai A, Piromsopa K. An innovative mobile application for wellness tourism destination competitiveness assessment: The research and development approach. HighTech and Innovation Journal (2023), 4(3), 592-616.

3. Auyporn W, Piromsopa K, Chaiyawat T. A Study of Distinguishing Factors between SME Adopters versus Non-Adopters of Cybersecurity Standard. International Journal of Computing and Digital Systems (February 2023), 189-198.

Asst. Prof. Sira Sriswasdi, Ph.D.

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ.āļŠāļīāļĢāļ° āļĻāļĢāļĩāļŠāļ§āļąāļŠāļ”āļīāđŒ

Education

â€Ē Ph.D. (Genomics and Computational Biology) University of Pennsylvania, Philadelphia, PA USA (2013)
â€Ē B.Sc. (Mathematics) Massachusetts Institute of Technology, Cambridge, MA USA (2008)

Research Interest

â€Ē Molecular evolution
â€Ē Mathematical modeling in computational biology

Publication

1. Preechakul, K., Sriswasdi, S., Kijsirikul, B. and Chuangsuwanich, E., 2022. Improved image classification explainability with high-accuracy heatmaps. iScience, 25(3).

2. Cosentino, S., Sriswasdi, S. and Iwasaki, W., 2024. SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models. Genome Biology, 25(1), p.195.

3. Sriswasdi, S., Yang, C.C. and Iwasaki, W., 2017. Generalist species drive microbial dispersion and evolution. Nature communications, 8(1), p.1162.

Asst. Prof. Pravee kruachottikul, Ph.D.

āļœāļđāđ‰āļŠāđˆāļ§āļĒāļĻāļēāļŠāļ•āļĢāļēāļˆāļēāļĢāļĒāđŒ āļ”āļĢ. āļ›āļĢāļ°āļ§āļĩāļĢāđŒ āđ€āļ„āļĢāļ·āļ­āđ‚āļŠāļ•āļīāļāļļāļĨ

Education

â€Ē āļ§āļ—.āļ”. (āļ˜āļļāļĢāļāļīāļˆāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāđāļĨāļ°āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ™āļ§āļąāļ•āļāļĢāļĢāļĄ) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2564
â€Ē M.M (Entrepreneurship and Innovation) Melbourne University, 2567
â€Ē āļ§āļĻ.āļĄ. (āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāđ€āļĄāļ„āļ„āļēāļ—āļĢāļ­āļ™āļīāļ„āļŠāđŒ) āļŠāļ–āļēāļšāļąāļ™āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāđāļŦāđˆāļ‡āđ€āļ­āđ€āļ‹āļĩāļĒ, 2555
â€Ē āļ§āļĻ.āļš. (āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāđ„āļŸāļŸāđ‰āļē) āļŠāļ–āļēāļšāļąāļ™āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļ™āļēāļ™āļēāļŠāļēāļ•āļīāļŠāļīāļĢāļīāļ™āļ˜āļĢ āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļ˜āļĢāļĢāļĄāļĻāļēāļŠāļ•āļĢāđŒ, 2547
â€Ē Certificate (Clinical Trials Fundamentals) Monash University, 2567
â€Ē Certificate (AI in Healthcare) Melbourne University, 2567

Research Interest

â€Ē Innovation management
â€Ē Digital health entrepreneurship
â€Ē Health technology commercialization

Publication

1. Meyer P, Kruachottikul P, Tantithamthavorn C, Kovitanggoon K, Chancharoen R, Phanomchoeng G. AI-Powered Telepresence Laboratory: Generative AI Co-Pilot for Automated Experiment Guidance and Instruction. INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION (Jaunary 2025), 41(6), 1412-1432.

2. Kruachottikul P, Yamyuan I, Tanmalaporn T, Noisri S, Sasithong S, et al. Immersive Learning Environment Platform: ChulaVerse’s 3D Interactive University. Engineering Journal (July 2025), 29(7), 17-33.

3. Kruachottikul P, Teamakorn P, Dumrongvute P, Hemrungrojn S, et al. MediGate: a MedTech product innovation development process from university research to successful commercialization within emerging markets. Journal of Innovation and Entrepreneurship (October 2024), 13(1), 71.

Wasin Laohawinit, M.D.

āļ™āļēāļĒāđāļžāļ—āļĒāđŒāļ§āļĻāļīāļ™ āđ€āļĨāļēāļŦāļ§āļīāļ™āļīāļˆ

Education

â€Ē āļ§āļ—.āļĄ. (āļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ”āđ‰āļēāļ™āļŠāļļāļ‚āļ āļēāļž), āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2567
â€Ē āļž.āļš. āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ 2560

Research Interest

â€Ē Diabetes care
â€Ē Health services research
â€Ē Clinical quality improvement

Publication

1. Nantavithya C, Prayongrat A, Laohavinij W, Shotelersuk K, et al. Cost-Effectiveness of Proton Versus Photon Therapy for Medulloblastoma Using Updated Clinical Outcomes. International Journal of Particle Therapy (September 2025), 17, 100754.

2. Manasnayakorn S, Annoppornchai P, Laohavinij W, Phanupak N, Suwan A, Suwajo P. Breast cancer screening awareness among transgender individuals in Bangkok, Thailand. International Journal of Transgender Health (February 2024), 26(1), 1-7.

3. Aekplakorn W, Neelapaichit N, Chariyalertsak S, Nonthaluck J, Laohavinij W, et al. Ideal cardiovascular health and all-cause or cardiovascular mortality in a longitudinal study of the Thai National Health Examination Survey IV and V. Scientific Reports (February 2023), 13(1), 2781.

Chavit Tunvirachaisakul, M.D., Ph.D.

āļ”āļĢ.āļ™āļēāļĒāđāļžāļ—āļĒāđŒāļŠāļēāļ§āļīāļ— āļ•āļąāļ™āļ§āļĩāļĢāļ°āļŠāļąāļĒāļŠāļāļļāļĨ

Education

â€Ē Ph.D. (Old Age Psychiatry), King’s College London, UK, 2563
â€Ē āļ­āļ§. (āļˆāļīāļ•āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒāļœāļđāđ‰āļŠāļđāļ‡āļ­āļēāļĒāļļ) āđāļžāļ—āļĒāļŠāļ āļē, 2563
â€Ē āļ§āļ§. (āļˆāļīāļ•āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒ) āđāļžāļ—āļĒāļŠāļ āļē, 2553
â€Ē āļ§āļ—.āļĄ. (āļˆāļīāļ•āđ€āļ§āļŠāļĻāļēāļŠāļ•āļĢāđŒ) āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2553
â€Ē āļž.āļš. āļˆāļļāļŽāļēāļĨāļ‡āļāļĢāļ“āđŒāļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒ, 2549

Research Interest

â€Ē Late-life depression
â€Ē Cognitive Impairment and Dementia
â€Ē Biomarkers and machine learning

Publication

1. Jirakran K, Vasupanrajit A, Tunvirachaisakul C, Almulla A. F, Kubera M, Maes M. Lipid profiles in major depression, both with and without metabolic syndrome: associations with suicidal behaviors and neuroticism. BMC psychiatry (April 2025), 25(1), 379.

2. Jirakran K, Almulla A. F, Jaipinta T, Vasupanrajit A, Tunvirachaisakul C, et al. Increased atherogenicity in mood disorders: a systematic review, meta-analysis and meta-regression. Neuroscience & Biobehavioral Reviews (January 2025), 169, 106005.

3. Maes A, Vasupanrajit A, Jirakran K, Zhou B, Tunvirachaisakul C, Almulla A. F. Simple dysmood disorder, a mild subtype of major depression, is not an inflammatory condition: Depletion of the compensatory immunoregulatory system. Journal of Affective Disorders (April 2025), 375, 75-85.