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5703 - 智慧醫療案例與實作 Smart Healthcare Case Studies


教育目標 Course Target

本課程目的是培養學生利用AI技術,解決跨領域問題的能力。首先由醫師針對重症疾病,包括急性呼吸窘迫、病患拔管預測、敗血症、病患出院預測等問題,對學生進行問題定義與背景知識介紹。透過跨域交流,讓醫師、教師、學生的溝通方式、專業術語、資料長相、預測技術等有充分的互動與理解。接續由資訊背景的老師以實際案例分享,說明各項疾病的AI應用。後續由醫師針對問題說明數篇文獻探討與分享討論後,學生開始分組,針對重症疾病進行病患狀況預測模型訓練,並討論如何實際臨床應用的可行性規劃與設計。期望透過實際醫療資料、跨域高頻率互動合作的模式下,養成學生以AI技術實際協助醫師進行病況預測的能力。 本課程主要養成學生以下能力: 1. 養成學生透過AI技術,開發智慧醫療相關系統的能力 2. 培養學生跨域合作,建構智慧醫療模型的實做能力 The purpose of this course is to cultivate students' ability to use AI technology to solve cross-domain problems. First, doctors define problems and introduce background knowledge to students regarding severe diseases, including acute respiratory distress, prediction of patient extubation, sepsis, prediction of patient discharge, etc. Through cross-domain communication, doctors, teachers, and students can fully interact and understand the communication methods, professional terminology, data appearance, prediction technology, etc. Teachers with information backgrounds will then share practical cases to explain the application of AI in various diseases. After the doctors discussed and shared several literatures on the problem, the students began to work in groups to train patient condition prediction models for severe diseases and discuss the feasibility planning and design of practical clinical applications. It is hoped that through actual medical data and cross-domain high-frequency interactive cooperation, students can develop their ability to use AI technology to actually assist doctors in predicting disease conditions. This course mainly develops students' following abilities: 1. Develop students’ ability to develop smart medical-related systems through AI technology 2. Cultivate students’ ability to collaborate across domains and construct smart medical models.


參考書目 Reference Books

1. AI 醫療 DEEP MEDICINE
作者:Eric Topol
ISBN:9789863126508
出版社:旗標
出版日期:2020/11/20

2. 各重症疾病期刊論文
1. AI Medical DEEP MEDICINE
Author: Eric Topol
ISBN: 9789863126508
Publisher: Flag
Publication date: 2020/11/20

2. Articles in various critical disease journals


評分方式 Grading

評分項目 Grading Method 配分比例 Grading percentage 說明 Description
課堂參與課堂參與
class participation
10
書面報告書面報告
written report
20
口頭報告口頭報告
Oral report
20
實作成品實作成品
Implemented finished product
50

授課大綱 Course Plan

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Course Information

Description

學分 Credit:0-3
上課時間 Course Time:Thursday/6,7,8[ST405]
授課教師 Teacher:傅彬貴/許瑞愷/吳杰亮/趙文震
修課班級 Class:資工碩1,2
選課備註 Memo:人工智慧、人工智慧應用
授課大綱 Course Plan: Open

選課狀態 Attendance

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目前選課人數為 4 人。

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