講題：From Clinical to AI - Developing AI Tools in Trauma Care

講者：林口長庚醫院外傷急症外科暨長庚大學醫學系兼任臨床副教授  鄭啟桐醫師

時間：2024.3.19 (二) 14:00-16:00

地點：人工智慧研究中心（管理大樓11樓）

線上直播： https://reurl.cc/QelMKZ

講者介紹：

Dr. Chi-Tung Cheng serves as an Associate Professor within the Department of Trauma and Emergency at Chang Gung Memorial Hospital, Linkou branch, and holds a Ph.D. in Biomedical Engineering. His academic journey includes a Visiting Scholar at the Johns Hopkins Malone Center for Engineering in Healthcare, highlighting his commitment to bridging the gap between engineering and medical sciences. As an accomplished trauma surgeon, Dr. Cheng is at the forefront of integrating cutting-edge technologies to enhance patient care in trauma and critical care settings. His pioneering work involves the development of AI-based tools designed to augment diagnostic accuracy in clinical environments. Dr. Cheng's scholarly contributions are prolific, spanning a wide array of disciplines, including medical informatics, diagnostic imaging, artificial intelligence, and computer science.
Award:
"Most Downloaded Paper Award 2019", European Society of Radiology
Outstanding teaching physician at Chang Gung Memorial Hospital, 2016
Resident Excellent Paper Award of Taiwan Gastroenterology Society, 2011
Resident Excellent Paper Award of Chang Gung Memorial Hospital, 2011
Resident Excellent Paper Award of Taiwan Gastroenterology Society
2020 The 17th National Innovation Award
2021 The 18th National Innovation Award

演講大綱：

Trauma represents a potentially life-threatening medical condition that requires prompt intervention to ensure patient survival and prompt identification of injured organs. Physicians working in this high-pressure environment must read and interpret a vast amount of information and images in a limited amount of time. Deep learning has been shown to be effective in several medical image domains, including hemorrhage detection in brain CT scans, fracture detection in chest and pelvic X-rays, and fluid detection in ultrasonography.
At the Linkou Chang Gung Memorial Hospital trauma department, our objective is to apply deep learning algorithms to various critical trauma image modalities in order to develop a computer-aided diagnosis system. Our team has successfully developed fracture detection models for pelvic X-rays, rib fracture detection models for chest X-rays, and spleen injury identification models for abdominal computed tomography.
Our future goal is to integrate this system into the clinical information system and apply these models to the trauma image warning system, thus providing a computer-assisted diagnosis of critical injuries to trauma patients in all hospitals. By diagnosing severe injuries early, we can improve the quality of trauma care and save patients' lives. 

主辦單位：人工智慧研究中心、智慧運算學院

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