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Research 61–90 of 1000+
- Learning From Success and Failure: Biologics for Non-approved Skin Diseases
- Learning to Read in Multilingual Malaysia: A Focus on Bahasa Melayu, Tamil and Chinese
- Machine learning-based steroid metabolome analysis reveals three distinct subtypes of polycystic ovary syndrome and implicates 11-oxygenated androgens as major drivers of metabolic risk
- Quantitative analysis and development of alopecia areata classification frameworks
- Amplitude-guided deep reinforcement learning for semi-supervised layer segmentation
- DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
- Analysis of modern approaches to hair care: An overview of products and techniques
- Severity Prediction of Hair Loss in Alopecia Areata with Hybrid Deep Learning Architecture
- eLife assessment: Spatiotemporal dynamics of sensory neuron and Merkel-cell remodeling are decoupled during epidermal homeostasis
- Experimental assessment of regenerative properties of platelet rich plasma on the human skin - a review
- Development and Assessment of an Artificial Intelligence–Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices
- Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach
- Ensemble of pre-learned deep learning model and an optimized LSTM for Alopecia Areata classification
- Exploring machine learning strategies for single-cell transcriptomic analysis in wound healing
- A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women
- How good is artificial intelligence (AI) at solving hairy problems? A review of AI applications in hair restoration and hair disorders
- Detecting shortcut learning for fair medical AI using shortcut testing
- Assessment the Effect of Ficus carica Leaf Extract on B16F10 Melanoma Cancer Cells: The Roles of p53, Caspase-3 & Caspase-9 on Induction of Intrinsic Apoptosis Cascade
- KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning
- An Early Hair Loss Detection and Prediction Method Based on Machine Learning
- Machine Learning-Driven Optimization of Therapeutic Substance Composition for High-Hardness, Fast-Dissolving Microneedles for Androgenetic Alopecia Treatment.
- Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative Model: Protocol for a Cross-sectional Study
- Research on Mental Stress Recognition of Depressive Disorders in Patients With Androgenic Alopecia Based on Machine Learning and Fuzzy K-Means Clustering
- Assessment of cardiovascular risk in patients with androgenetic alopecia using high-sensitivity C-reactive protein and lipoprotein a
- Qualitative and Quantitative Assessment of Taste and Smell Changes in Patients Undergoing Chemotherapy for Breast Cancer or Gynecologic Malignancies
- Data-Driven Machine-Learning Methods for Diabetes Risk Prediction
- Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods
- Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
- Introductory Chapter: Learning and Recognizing the Post-COVID Syndromes
- Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation