research Advanced Intelligent Systems for Surgical Robotics
Surgical robots have improved but still can't perform tasks or make decisions on their own.
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210-240 / 1000+ resultsresearch Ensemble of pre-learned deep learning model and an optimized LSTM for Alopecia Areata classification
The new model improves Alopecia Areata classification accuracy to 93.1%.
research Alopecia Areata Incognita
Alopecia areata incognita causes sudden hair thinning, responds well to steroids, and is more common in those with genetic hair loss conditions.
research The Follicle Inference Engine (FIE): A stochastic digital twin and optimal experimental design framework for androgenetic alopecia
research Analyse trichoskopischer Bilder mit tiefen neuronalen Netzen zur Diagnose und Aktivitätsbewertung von Alopecia areata – eine retrospektive Studie
Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
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 199 Computer vision AI-based androgenetic alopecia analysis using a novel mobile web app
The MDhair app accurately assesses hair loss severity with 94% accuracy.
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 Alopecia areata incognito: an elusive disease
Accurate diagnosis of alopecia areata incognito requires trichoscopy and histopathology.
research Chemistry42: An AI-Driven Platform for Molecular Design and Optimization
Chemistry42 effectively creates and optimizes new molecules for drug discovery.
research Alopecia Areata Incognita: Current Evidence
Alopecia areata incognita causes sudden hair loss but usually improves with topical steroids.
research Medical Reasoning with Large Language Models: A Survey and MR-Bench
Large language models struggle with accurate clinical decision-making compared to real-world needs.
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 Precision and Personalized Medicine in Transdermal Drug Delivery Systems: Integrating AI Approaches
AI-enhanced smart patches can personalize drug delivery for better treatment outcomes.
research A Comparative Analysis of Large Language Model Accuracy for Image-Based Hair Disease Identification in Diverse Skin Tones
ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.
research A Comparative Study of Machine Learning Algorithms in Predicting Mental Disorders
Machine learning can accurately predict mental disorders.
research LB1040 Machine learning-based predictive model with routine blood work identifies moderate-severe alopecia areata
Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.
research Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.
research The Epochal Transition Vol.1 No.8 (March 2026) 时代跃迁 第八期
The "Danti Original Source" method can reverse androgenetic alopecia.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
research DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network
The DNN-DTIs method accurately predicts drug-target interactions and is useful for drug repositioning.
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 Patients with profuse hair shedding may reveal anagen hair dystrophy: a diagnostic clue of alopecia areata incognita
Some people with heavy hair shedding might actually have a hidden form of alopecia, which can be identified by specific hair changes.
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 706 Predictive modeling of patient response to JAK/STAT inhibitors and dynamic patient-matching
Machine learning can predict how well patients with alopecia areata will respond to certain treatments.
research Modeling share dynamics by extracting competition structure
The model can predict website market shares by identifying competition among them.
research A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions
A new neural network helps identify key regulators in cell changes, aiding in understanding diseases and finding new treatments.
research 427 Discerning patient perspectives towards specific treatments of alopecia areata using artificial intelligence
Patients using social media have mixed feelings about alopecia treatments, noting hair growth but also frustration with treatment recurrence.
research ANÁLISES COMPUTACIONAIS PREDITIVAS COMO UM NOVO BIOPODER: MODIFICAÇÕES DO TEMPO NA SOCIEDADE DOS SENSORES
Predictive computational analyses have evolved biopower by using technology to track and predict individual and group behaviors.
research Performance Evaluation of the Generative Pre-trained Transformer (GPT-4) on the Family Medicine In-Training Examination
GPT-4 performs well on medical exams but still needs human doctors for critical thinking.