February 2026 in “Expert Review of Endocrinology & Metabolism” This review discusses the dermatologic manifestations and management of polycystic ovary syndrome, underscoring the need for mechanism-based, personalized treatments and integrated mental health support, but reports no new clinical results.
This study evaluated machine-learning models to predict PCOS among reproductive-aged women in Bangladesh, finding that the XGBoost model achieved high accuracy (99.63%) and effectiveness, particularly when prioritizing clinical features over psychological ones in the predictive process.
3 citations
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May 2023 in “Precision clinical medicine” This study analyzed gene expression data to identify key genes involved in severe forms of alopecia areata, discovering four immune monitoring genes (LGR5, SHISA2, HOXC13, S100A3) with potential for early diagnosis and better understanding of the disease's biological mechanisms.
5 citations
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March 2022 in “Clinical Cosmetic and Investigational Dermatology” This study proposed a model that accurately predicts skin condition using genotype information and machine learning, suggesting potential for creating customized cosmetics.
March 2024 in “medRxiv (Cold Spring Harbor Laboratory)” This study found that faster algorithms for inferring ancestry in genomic data can better capture historical and functional insights into genome variation than traditional methods in large datasets like the UK Biobank.
