歯内科における診断,治療,および予測における人工知能:包括的な文献レビュー
Keina Kun1, Nathaly Adriana Gonzalez1, Gianella Malla1
1Department of Endodontics, University of Cuenca, Faculty of Dentistry, Ecuador.
European endodontic journal
|February 13, 2026
まとめ
人工知能 (AI) は,診断,治療計画,結果予測を向上させることで,内歯科を大幅に強化しています. 人工知能は歯科専門家に高度なツールを提供していますが,データ要件やコストなどの課題は,より広範な臨床採用のためにさらなる研究を必要とします.
科学分野:
- 歯科 歯科は歯科を専門とするものです.
- 人工知能 (AI) とは,人工知能 (AI) のことです.
- メディカルイマージング (医学イメージング)
背景:
- 人工知能 (AI) は,エンドドンティクスを含む様々な医療分野にますます統合されています.
- AIアプリケーションは,診断の正確性,治療計画,およびエンドドントの手続きにおける結果の予測を向上させることを目的としています.
研究 の 目的:
- エンドドンティクスにおけるAIアプリケーションの包括的なレビューを実施する.
- 診断,臨床意思決定の最適化,治療結果の予測におけるAIの役割を分析する.
- エンドドンティクスにおけるAIの現在の限界と将来の発展の分野を特定する.
主な方法:
- 主要な科学データベース (PubMed,Scopus,ScienceDirect,Google Scholar) で体系的な文献検索が行われました.
- 2016年から2025年の間に英語で出版された研究が選択され,重複と無関係な記事は除外されました.
- レビューには,診断,治療,および予後におけるAIの応用に焦点を当てた51の関連記事が含まれました.
主要な成果:
- AIモデル,特にコンボリューションニューラルネットワーク (CNN) は,X線写真やコンビビームコンピュータトモグラフィー (CBCT) による近辺病変と垂直根骨折の検出において>90%の精度を達成します.
- ディープラーニングモデルは,複雑な根管の解剖を正確に識別し,運河の長さを決定する際に伝統的な電子アペックスロケータを上回ります.
- AIモデルは,治療後の痛みを予測する高精度 (95.6%) と,エンドドントリートメントの成功率を示しています.
結論:
- AIは,診断能力,治療計画精度,および予後精度を向上させることで,内歯科学に革命を起こしています.
- 現在の制限には,広範囲のデータセットの必要性,高い実装コスト,自律的な開発の欠如が含まれます.
- これらの課題に取り組むことは,AIを日常的な内歯科臨床実践にシームレスに統合するために不可欠です.
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