October 2025 in “Frontiers in Artificial Intelligence” 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.
March 2021 in “The British Journal of Psychiatry” The abstract for this research is not provided, so results or conclusions from this study are not available.
September 2016 in “Journal of Dermatological Science” Polarizing light microscopy can easily and reliably diagnose congenital keratinizing disorders like Netherton syndrome.
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September 2024 in “arXiv (Cornell University)” This study reviews methods to ensure the reliability of machine learning models in medical imaging, focusing on bias detection, data drift assessment, and accuracy estimation without ground truth labels to enhance integration into clinical settings.
April 2026 in “Brain Sciences” This pharmacovigilance study analyzed FAERS data and found that finasteride is more frequently associated with neuropsychiatric reactions like depression and suicide risk, especially in younger men using it for alopecia, compared to dutasteride.