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- Attention Balanced Multi-Dimension Multi-Task Deep Learning for Alopecia Recognition
- A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer
- A machine learning approach for non-invasive PCOS diagnosis from ultrasound and clinical features
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
- Spectrum and signals of medication-associated cognitive disorder: a comprehensive disproportionality analysis with cross-database validation
- AB-MTEDeep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata
- Endocrine Treatment of Transsexual Persons:An Endocrine Society Clinical Practice Guideline
- Quantitative analysis and development of alopecia areata classification frameworks
- A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women
- Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation
- Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative Model: Protocol for a Cross-sectional Study
- Drug Repurposing against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study
- Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
- Development of a Predictive Model for Iron Levels in Bovine Muscle Tissue Using Hair as a Predictor
- Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
- A State-of-the-Art Overview on (Epi)Genomics and Personalized Skin Rejuvenating Strategies
- Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
- From Diagnosis to Prognosis: A Scoping Review of Artificial Intelligence in Alopecia Research
- MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network
- JAK-centric explainable few-shot gene-expression diagnosis framework for alopecia via MultiPLIER priors and relation-style set-to-set comparison
- Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging
- Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
- HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
- Application of big data analytics in minoxidil drug development: a data-driven model for predicting efficacy and side effect risks
- Advances and Prospects for Hydrogel-Forming Microneedles in Transdermal Drug Delivery
- Cutaneous melanoma, prostate-specific antigen testing and the subsequent risk of prostate cancer diagnosis: a prospective analysis of the 45 and Up Study
- 3D organotypic skin models recapitulate autoantibody-driven pemphigus pathomechanisms and targeted therapeutic response
- Past, Present and Future Perspectives of Forensic Genetics
- Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets