デジタルヘルスにおける人工知能 (AI) ベースのチャットボットの活用:体系的なレビュー
Shi Feng1, Xiufang Leah Li1, Alexandra Nicole Wake1
1School of Media and Communication, RMIT University, Melbourne, Victoria, Australia.
PLOS digital health
|February 12, 2026
まとめ
人工知能 (AI) ベースのチャットボットは,革新的な医療ソリューションを提供しています. この体系的なレビューでは,それらの応用と有効性を評価し,将来の開発のための主要な研究分野と限界を特定します.
科学分野:
- 医療情報工学 医療情報工学
- 人工知能 (AI) とは,人工知能 (AI) のことです.
- 人とコンピュータの相互作用です.
背景:
- ヘルスケアセクターは,ますます人工知能 (AI) ソリューションを採用しています.
- AIベースのチャットボットは,健康上の課題に取り組むための重要なツールとして浮上しています.
- ディープラーニングアーキテクチャは,AIヘルスケアアプリケーションの進歩を推進しています.
研究 の 目的:
- 医療におけるAIベースのチャットボットに関する既存の研究を体系的にレビューする.
- AIチャットボットの現在のアプリケーションと評価方法を特定する.
- チャットボットの有効性や倫理的な影響に関する懸念に対処するためです.
主な方法:
- 8つの主要なデータベースから348件の論文を体系的に文献レビューした.
- 分析は,医療分野におけるAIベースのチャットボットに焦点を当てた.
- 4つの主要な研究分野を特定しました:テキスト品質,臨床有効性,ユーザーエンゲージメント,安全性.
主要な成果:
- AIベースのチャットボットは,4つの主要な研究分野に適用されています.
- ランダム化対照試験 (RCT) の数には大きなギャップがある.
- 理論的枠組みの限られた使用は,堅実なパフォーマンス評価を妨げます.
結論:
- 医療におけるAIチャットボットの可能性を最適化するためにさらなる研究が必要である.
- RCTや理論的フレームワークの不足に対処することは,チャットボット開発を進めていく上で極めて重要です.
- 将来の方向は,倫理的な影響を考慮しながら,臨床的有効性,ユーザーエンゲージメント,および安全性の強化に焦点を当てるべきです.
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