research How Can Clinicians Leverage Vibe Coding for Machine Learning and Deep Learning Research?
Clinicians can use vibe coding to easily engage in machine learning research without needing to know Python.
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research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
research Machine learning predicts scarring progression in lichen planopilaris: A multidimensional model integrating trichoscopy, vitamin D, and diagnostic timelines
A machine learning model can predict scarring in lichen planopilaris using factors like vitamin D levels and diagnostic delay.
research Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study
Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.
research Amplitude-guided deep reinforcement learning for semi-supervised layer segmentation
The new method improves accuracy in segmenting scalp tissue layers.
research Ewha Medical Journal’s inclusion in PubMed Central and PubMed, and artificial intelligence and guidelines in this issue
The Ewha Medical Journal is now in PubMed, has an AI article editor, and offers Korean reporting guidelines.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.
research Big Self-Supervised Models Advance Medical Image Classification
Self-supervised learning improves medical image classification accuracy.
research Advancements in Dermatological Imaging Modalities
New imaging technologies improve skin diagnosis but face cost and training challenges.
research Past, present, and future of global research on artificial intelligence applications in dermatology: A bibliometric analysis
AI in dermatology is growing rapidly, showing promise in diagnosing skin conditions as accurately as dermatologists.
research Efficient integration of human skin single-cell RNA sequencing data
A comprehensive human skin cell atlas was created to better understand skin biology and disease.
research Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.
research Knowledge Mapping of Drug Repositioning’s Theme and Development
Drug repositioning can save time and money but needs more support.
research Identification of Drug-Disease Associations Using Information of Molecular Structures and Clinical Symptoms via Deep Convolutional Neural Network
A new model can predict drug-disease links well, helping drug research.
research A machine learning approach for non-invasive PCOS diagnosis from ultrasound and clinical features
Machine learning can accurately diagnose PCOS non-invasively using clinical and ultrasound features.
research Phenotype-Specific Lifestyle Prediction for PCOS Using Machine Learning Multi-Class Classification and SHAP Explainability
Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.
research Deep Insight of Design, Mechanism, and Cancer Theranostic Strategy of Nanozymes
Nanozymes show promise for effective and safe cancer treatment.
research Bone marrow-derived vasculogenesis leads to scarless regeneration in deep wounds with periosteal defects
Using gelatin sponges for deep skin wounds helps bone marrow cells repair tissue without scarring.
research ADVANCES IN FUNCTIONAL NEUROSURGERY – MACHINE LEARNING, NEURAL ENGINEERING AND ROBOTICS IN TREATMENT OF NEURODEGENERATIVE DISORDERS
AI and robotics are improving treatment and monitoring of neurodegenerative disorders like Parkinson's.
research Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
research Data-Driven Machine-Learning Methods for Diabetes Risk Prediction
Machine learning can effectively predict type 2 diabetes risk.
research Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging
A new tool can analyze hair to detect changes due to hormones, genetics, and aging.
research LEVERAGING MACHINE LEARNING METHODS IN PREDICTING AND ANALYZING THE ASSOCIATION BETWEEN DIETARY INFLAMMATORY INDEX AND ALOPECIA
Inflammatory diets may increase the risk and severity of alopecia areata.
research Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach
Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
research A Machine Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
The system can automatically identify different hair and scalp conditions using machine learning.
research Machine learning for nanozyme development in anti‐inflammatory applications
Rational design strategies are crucial for developing effective nanozymes for anti-inflammatory uses.
research 3D organotypic skin models recapitulate autoantibody-driven pemphigus pathomechanisms and targeted therapeutic response
The 3D skin model mimics pemphigus vulgaris and helps test treatments.