December 2023 in “International Journal of Pharmaceutics” This study developed innovative silica/natural polysaccharide hybrid nanoparticles encapsulating plant-derived 5-alpha-reductase inhibitors, reporting effective controlled release at hair follicle pH and lower cytotoxicity, suggesting a promising delivery system for antiandrogenic treatments.
3 citations
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April 2025 in “International Journal of Pharmaceutics” Nanocrystals improve alopecia areata treatment by better targeting hair follicles.
3 citations
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September 2023 in “PeerJ Computer Science” This study introduced an innovative metric for assessing college students' mental health, incorporating temporal perception and a hybrid clustering algorithm, and found it achieved over 90% accuracy, outperforming existing methods in evaluating mental health during public health challenges.
April 2026 in “International Journal of Engineering Research and Science & Technology” This study reports that an Explainable AI-based hair health prediction system using a novel hybrid model outperformed traditional machine learning methods, achieving high accuracy in predicting key factors and providing personalized recommendations.
June 2026 in “Zenodo (CERN European Organization for Nuclear Research)” In this study, researchers developed a hybrid deep learning model called ScalpViT that accurately diagnosed scalp diseases with 94.3% accuracy, surpassing existing methods like ResNet-50 and EfficientNet-B3, and providing visual explainability for clinicians using GradCAM and Attention Rollout techniques.
