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許凱程 - Transforming Smart Healthcare with Generative AI - 2023 Taiwan AI Academy Conf

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Transforming Smart Healthcare with Generative AI

Time / Place:

⏱️ 09/15 (Fri.) 15:30-16:00 at R3 - 1st Conference Room ( Academia Sinica Academic Activities Center )

Abstract:

The speech provided a compelling insight into the potential of Generative AI to revolutionize healthcare, focusing on a pioneering collaboration between the China Medical University Hospital and Microsoft Taiwan.

The gHi System, a groundbreaking AI solution born out of this collaboration, is globally recognized as the first generative AI medical system constructed in Chinese. Utilizing Microsoft's Azure platform and the cutting-edge language model GPT-4, the gHi System significantly reduces time spent on medical record-keeping, improving administrative efficiency and freeing medical professionals to focus more on patient care.

The speech further highlighted how generative AI can transcend record-keeping by aiding in predicting disease patterns, personalizing treatment plans, and facilitating communication in patient care.

In summary, the speech painted a future of smart healthcare where the intersection of Generative AI and medicine promotes more efficient, effective, and patient-centric medical practices. It highlighted the impressive achievements of collaborative technological innovation, opening up a conversation on the future of smart healthcare.

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Biography:

許凱程
  • 許凱程 Kai-Cheng Hsu
    Website: https://www.cmuh.cmu.edu.tw/Doctor/DoctorInfo?docId=D35842
  • China Medical University Hospital / Artificial Intelligence Center / Director
  • Dr. Kai-Cheng Hsu is the Director of the Artificial Intelligence Center (AIC) for Medical Diagnosis at China Medical University Hospital (CMUH) and an Attending Physician at the Neurology Department of CMUH. He acquired a Medical Doctor from National Taiwan University, a Master of Electrical Engineering, and a Ph.D. in Chemical Engineering from National Chung Cheng University. He visited the National Institutes of Health (USA) for Medical Artificial Intelligence training from 2018 to 2020. His areas of research interest include artificial intelligence applications in medical images, biomedical signals, electronic health records, and bioinformatics. His goal is to combine his expertise in medicine and engineering to apply AI to develop products for advancing biomedical technology. He has led AIC to develop dozens of AI algorithms for clinical use in CMUH.

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