What question did this study set out to answer?

This research aims to analyze the transformative impact of machine learning on disease detection and treatment practices.

The role of machine learning in early detection, accurate diagnosis, and timely treatment of diseases

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Comprehensive analysis reveals machine learning enhances early detection and diagnosis in healthcare, suggesting improved patient outcomes.

This research aims to analyze the transformative impact of machine learning on disease detection and treatment practices.
Discusses key machine learning paradigms and their applications in healthcare.
Explores ML's role in early detection and diagnosis for diseases like cancer and diabetic retinopathy.
Examines challenges in data quality, interpretability, ethics, and regulatory issues.
ML algorithms demonstrate superior performance in analyzing medical imaging and genomics data.
Successfully identify pre-symptomatic patterns in diseases, enhancing timely interventions.
Concludes that ML will support clinicians in predictive and personalized healthcare approaches.

Shrivastava et al. (2026) studied this question.

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Comprehensive analysis reveals machine learning enhances early detection and diagnosis in healthcare, suggesting improved patient outcomes.