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題名：人工智慧輔助之遠距傷口照護決策支援系統
作者：張惇皓
作者(外文)：Chang, Dun-Hao
校院名稱：元智大學
系所名稱：資訊管理學系
指導教授：詹前隆
學位類別：博士
出版日期：2024
主題關鍵詞：遠距醫療；傷口照護；人工智慧；決策支援系統；Telemedicine；Wound care；Artificial intelligence；Clinical decision support system
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慢性傷口的照護因為漫長的癒合期，對於照護者或是醫療系統造成不小的挑
戰和負擔。這些慢性傷口的病患，如褥瘡或是糖尿病潰瘍，往往因為行動不便而
無法即時的獲取醫療資源。遠距醫療雖然可以彌補這些照護上的不足，但現行的
遠距醫療也受到特定時間和區域的限制，使得普及性不高，也無法適用到每一個
居家照護的環境。
因此我們目標要開發一個人工智慧輔助的臨床決策支援系統，來提供自動的
傷口判斷和相關的照護建議。在此研究中，我們由傷口影像處理著手，經由醫師
標記的傷口照片，建立深度學習的模組，達成傷口的擷取、組織分類的判斷及傷
口測量。結合其他照護者所輸入的資訊，如傷口滲液、氣味、周邊皮膚情況等，
醫師由此所編寫而成的照護建議形成一決策支援系統。最後將此系統進一步結合
雲端平台，讓病患或照護者可上傳傷口照片，並在醫師或是傷口照護師的監管之
下，得到系統分析的傷口照護建議和回饋。
建立完成的系統名為 Ulcer Care。我們在慢性傷口的病患進行臨床的隨機分
派研究。在臨床試驗的初始報告中，我們發現使用遠距傷口照護的病患和一般傷
口照護組有相似的傷口癒合率，但有較少的就醫次數，照護者也有較高的生活品
質。人工智慧模組的表現雖不如訓練集資料優異，但未來仍可經由多元資料訓
練、開發訓練新的模組來增加準確率。我們期待此系統未來有更多的臨床應用。
Management of chronic wounds is a challenge and burden for both caregivers and healthcare systems because the healing process is time consuming with high cost. Patients with chronic wounds, such as pressure ulcers or diabetic foot ulcers are usually disabled and have difficulties in seeking medical resources. Telemedical wound care can fulfil this unmet need. However, current telemedicine has certain time and region limitsand has not been widely available for every home care setting.
Therefore, we aim to develop an artificial intelligence assisted clinical decision support system (AI-CDSS) to provide automatic wound assessment and relevant wound care recommendations. In this study, we started from wound image processing. Based on doctor labeled images, we trained the deep learning models to perform wound segmentation, tissue classification and wound measurement. In combination with other wound information input by caregivers, such as wound discharge, smell and peri-wound conditions, the wound care recommendations could be developed by the doctors, forming a decision support system. Finally, the AI-CDSS would be connected to a cloud platform, allowing the patients or caregivers to upload the wound images and obtain feedback from the AI-CDSS under the supervision of doctors or wound specialists.
The established AI-CDSS telemedical platform named “Ulcer Care” (UC). We
vconducted a clinical randomized control trial, comparing the UC users with standard care in chronic wound patients. In our preliminary report, we found the UC users had similar wound healing rate but fewer clinic visits, and their caregivers had better quality of life. Although the AI system couldn’t achieve the same performance as the training dataset, it cab be improved by diverse data training with new deep learning models. We are looking forward to more clinical application with UC.
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