頁籤選單縮合
| 題 名 | AI在開發中國家健康領域管理中的應用=AI Application in Health Management in Developing Countries |
|---|---|
| 作 者 | 鍾采璇; | 書刊名 | 國際開發援助現場季刊 |
| 卷 期 | 20 2025.06[民114.06] |
| 頁 次 | 頁23-31+8 |
| 專 輯 | 全球智慧醫療發展探究 |
| 分類號 | 312.83 |
| 關鍵詞 | 人工智慧; 公共衛生; 健康管理; 醫療資源分配; 開發中國家; |
| 語 文 | 中文(Chinese) |
| 中文摘要 | 人工智慧(AI)正迅速成為提升醫療與公共衛生服務的關鍵技術,尤其是在醫療資源有限的開發中國家。本文先整合國際報告與學術研究,梳理AI在疾病預防、遠距醫療、醫療資源分配與健康教育四大領域的核心應用;再透過作者於非洲獅子山共和國與索馬利蘭的實務經驗,說明決策感知式機器學習(Decision-Aware Learning)、大型語言模型(LLM)及強化學習(RL)等AI相關技術如何實質提升醫療服務效率與公平性。儘管前景可期,資料不足、基礎設施薄弱、資金與人才匱乏,以及法規倫理框架的不完善,仍限制了AI在資源有限環境下的落地實現。要收穫AI技術的紅利並避免資料隱私侵犯、演算法偏見與醫療不平等擴大等風險,未來發展應聚焦於強化基礎建設、培育在地人才、制定合適的監管政策,確保AI技術的倫理性與普惠性,實現健康公平與永續發展的目標。 |
| 英文摘要 | AI is becoming a pivotal tool in advancing healthcare and public health services, particularly in resource-limited developing countries. Drawing from international research and personal field experience in Sierra Leone and Somaliland, the author outlines four key application areas: disease prevention, telemedicine, healthcare resource allocation, and health education. Specific AI technologies such as decision-aware learning, large language models (LLMs), and reinforcement learning (RL) have shown promise in improving service efficiency and equity. However, realworld implementation is constrained by data scarcity, fragile infrastructure, limited funding and talent, and insufficient regulatory and ethical frameworks. To unlock AI’s full potential while safeguarding against data privacy violations, algorithmic bias, and increased health inequality, future development must focus on strengthening infrastructure, cultivating local talent, and establishing ethical and inclusive regulatory systems that promote health equity and sustainability. |
本系統中英文摘要資訊取自各篇刊載內容。