The role of explainable artificial intelligence in disease prediction: a systematic literature review and future research directions

Explainable Artificial Intelligence (XAI) enhances transparency and interpretability in AI models, which is crucial for trust and accountability in healthcare. A potential application of XAI is disease prediction using various data modalities. This study conducts a Systematic Literature Review (SLR)...

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Veröffentlicht in:	BMC medical informatics and decision making Jg. 25; H. 1; S. 110 - 17
Hauptverfasser:	Alkhanbouli, Razan, Matar Abdulla Almadhaani, Hour, Alhosani, Farah, Simsekler, Mecit Can Emre
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 04.03.2025 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Accountability Artificial Intelligence Clinical medicine Data integration Decision making Diagnosis Disease Disease prediction Disease recognition Diseases Explainable artificial intelligence Forecasts and trends Health aspects Health care Health Informatics Healthcare AI Humans Information Systems and Communication Service Literature reviews Machine learning Management of Computing and Information Systems Medical imaging equipment Medical personnel Medicine Medicine & Public Health Physiology Predictions Research methodology Systematic Review Transparency United Arab Emirates XAI United Arab Emirates Decision support systems XAI Machine learning Explainable artificial intelligence Healthcare AI Patient safety Risk management Disease recognition Disease prediction
ISSN:	1472-6947, 1472-6947
Online-Zugang:	Volltext
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