Hairsentinel: A Time-Aware Anomaly Detection Framework for Forecasting Hairfall Trends Using Temporal Fusion Transformers

October 2025 in “ Frontiers in Artificial Intelligence ”

A. Anny Leema, T. Saktheshwaran, G. Abitha Sri, P. Balakrishnan

hairfall Temporal Fusion Transformers anomaly detection hormonal fluctuations

Studysummary This study evaluated a novel, user-friendly approach for detecting hairfall trends over time using machine learning models. The Temporal Fusion Transformer model demonstrated high accuracy in identifying anomalies in hair shedding patterns, potentially aiding in the early detection of health risks related to hormonal fluctuations.

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