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Author

M. Toma

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Open access Aug 2026

Electrocardiogram Abnormality Classification From Summary Statistics With Patient‐Level Validation and Process‐Focused Evaluation

ABSTRACT Background Machine learning (ML) applications in clinical medicine are vulnerable to data leakage, particularly temporal leakage from post‐diagnostic features and patient‐level leakage from improper partitioning, compromising electrocardiogram (ECG) abnormality detection systems. This study addresses these vul...

Sungjoon Hong, Christina Hartnett, Michael Ruane et al. · 0 citations
Open access Sep 2026

Perspectives on the Limits and Clinical Alignment of Medical AI from Population Statistics to Individual Care

The clinical integration of artificial intelligence has outpaced the development of robust evaluative frameworks, raising critical safety concerns. This perspective establishes a clear taxonomy distinguishing probabilistic language models from deterministic classifiers and applies a multi-dimensional combinatorial mode...

M. Toma, David Yusupov · 1 citation
Open access Jul 2026

Channel reduction in AdaBoost ensemble models for energy-efficient ambulatory seizure detection

Analysis of a feature reduction strategy for a 100-tree AdaBoost ensemble model applied to binary seizure detection using the Bangalore EEG Epilepsy Dataset shows that strategic channel reduction based on feature importance analysis can improve computational efficiency while maintaining comparable seizure detection per...

Aangi J. Shah, M. Toma · 0 citations

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