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.
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research A DEEP LEARNING APPROACH FOR DIAGNOSIS OF COVID-19 INFECTION AND ITS RELATED FACTORS: A POPULATION-BASED STUDY
The random forest model effectively helps diagnose COVID-19 using key factors like age and symptoms.
research 200 Deep learning model to predict sentinel lymph node status in melanoma patients
The AI model somewhat predicts lymph node status in melanoma patients using skin sample images.
research 574 A deep learning classifier for the analysis of tiger tail banding in trichothiodystrophy
A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.
research A machine learning and network framework to discover new indications for small molecules
The model successfully predicted new uses for existing drugs, like using certain hormonal and heart medications for respiratory and Parkinson's diseases, and a cancer drug for diabetes.
research Improving preparation for scalp cooling: Learning from women undergoing chemotherapy for early‐stage breast cancer—The COOL study
Comprehensive information and trained nurses are crucial for a better scalp cooling experience during chemotherapy.
research Neurospectrum: A Geometric and Topological Deep Learning Framework for Uncovering Spatiotemporal Signatures in Neural Activity
Neurospectrum effectively analyzes neural signals to predict and identify brain activity patterns better than traditional methods.
research Integrating Biomarkers from Correlation Analysis and Metric Learning for Hair Loss Classification
Combining biomarker analysis and advanced algorithms improves hair loss detection accuracy.
research Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
The framework helps predict adverse effects of blood thinners, improving drug selection for atrial fibrillation.
research Advancing Hair Disease Diagnostics: A Deep Learning Approach Using Inception-ResNet v2 for Multi-Class Classification
The model accurately identifies hair diseases using deep learning.
research The Hair Cell Analysis Toolbox: A machine learning-based whole cochlea analysis pipeline
The Hair Cell Analysis Toolbox automates and improves the analysis of cochlear hair cells using machine learning.
research A discriminant multi-scale histopathology descriptor using dictionary learning
The new image descriptor helps identify skin cancer structures with good accuracy.
research Hair Tone Estimation at Roots via Imaging Device with Embedded Deep Learning
The device accurately estimates natural hair color at the roots in real time.
research Using Pork Skin as a Practice Medium for Learning Hair Transplantation Techniques
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.
research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research Drug Repurposing against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study
Afatinib, neratinib, and zanubrutinib could be effective against KRASG12C-mutant tumors.
research Treatment options and emotional well-being in patients with rosacea: An unsupervised machine learning analysis of over 200,000 posts
Rosacea patients often discuss treatments and emotional struggles online, highlighting the need for professional support.
research Innovative approaches to baldness detection and management with artificial intelligence and machine learning
research Global Research Trends for Platelet-Rich Plasma: A Science Mapping with Machine Learning Techniques
The USA, China, Italy, and Türkiye lead in diverse PRP research, focusing on healing and pain management.
research Alteration of neonatal Allopregnanolone levels affects exploration, anxiety, aversive learning and adult behavioural response to intrahippocampal neurosteroids
Changing Allopregnanolone levels in newborns affects adult behavior and anxiety.
research Construction of regulatory network for alopecia areata progression and identification of immune monitoring genes based on multiple machine-learning algorithms
Researchers found four genes that could help diagnose severe alopecia areata early.
research Investigation on the Mechanism of Platycladus orientalis in the Treatment of Androgenetic Alopecia Based on Machine Learning and Molecular Dynamics
research What do users in a polycystic ovary syndrome (PCOS) forum think about the treatments they tried: Analysing treatment sentiment using machine learning
PCOS forum users view lifestyle changes and supplements positively, but have mixed feelings about contraceptive pills.
research Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning
Four genes are potential markers for hair loss condition alopecia areata, linked to a specific type of cell death.
research Generating detailed intercellular communication patterns in psoriasis at the single-cell level using social networking, pattern recognition, and manifold learning methods to optimize treatment strategies
New insights into cell communication in psoriasis suggest innovative drug treatments.
research How to Assess Dermatology Resident Surgical Training: New Techniques
New evaluation tools are needed for better surgical training in dermatology residency programs.
research PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery
PandaOmics uses AI to find new disease treatment targets and biomarkers.
research Progesterone promotes the survival of newborn neurons in the dentate gyrus of adult male mice
Progesterone helps adult male mice grow more neurons and improves memory.
research Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.