Transforming healthcare with AI: a systematic review of predictive modeling for early disease detection and management

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Systematic review highlights performance metrics and stakeholder insights, indicating integration challenges.

AI-driven predictive modeling achieves accuracies between 88% to 98%, reflecting high diagnostic performance in healthcare.
Out of 24 studies, 72% exceeded AUC-ROC scores of 0.90, suggesting robust predictive capabilities across various diseases.
Only 33% of studies reported external validation, highlighting a gap in model reliability and assessment practices.
Significant barriers such as workflow integration and ethical concerns persist, calling for interdisciplinary collaboration in AI adoption.

Zafeer et al. (2025) studied this question.

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