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.
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research Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
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 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 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 Severity Prediction of Hair Loss in Alopecia Areata with Hybrid Deep Learning Architecture
The model accurately predicts hair loss severity in alopecia areata.
research A discriminant multi-scale histopathology descriptor using dictionary learning
The new image descriptor helps identify skin cancer structures with good accuracy.
research A comparative study of linear and nonlinear ANNs as classifiers of animal hair fibers
Nonlinear artificial neural networks are better at identifying different types of animal hair than linear ones.
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study
Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
research Hair Loss Diagnosis Using Artificial Neural Networks
Neural networks can effectively predict hair loss.
research Deep Learning-based Automatic System for Diagnosis and Classification of Skin Dermatoses
The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
research Predicting Hair Loss with AI: A Deep Learning Framework Combining Genetic and Scalp Health Data
AI can predict hair loss by analyzing genetic, scalp, and lifestyle data.
research 198 Reliable and interpretable segmentation for remote assessment of atopic dermatitis severity using digital images
The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.
research Deep skin diseases diagnostic system with Dual-channel Image and Extracted Text
The AI model DIET-AI effectively diagnoses skin diseases as well as doctors.
research The Dark Side of the Language: Pre-trained Transformers in the DarkNet
Pre-trained Transformers need extreme retraining to perform well on DarkNet data.
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 Computer aided classification of female androgenetic alopecia-an image processing and analysis system
research Innovative approaches to baldness detection and management with artificial intelligence and machine learning
research The Dark Side of the Language: Syntax-Based Neural Networks Rivaling Transformers in Definitely Unseen Sentences
Syntax-based neural networks can match Transformers in handling unseen sentences.
research Multiscale Morphological Reconstruction for Hair Removal in Dermoscopy Images
The method accurately detects and removes hair from skin images to improve melanoma diagnosis.
research Scalp disease analysis using deep learning models
Deep learning models can analyze scalp diseases effectively.
research FRCNN based Deep Learning for Identification and Classification of Alopecia Areata
The model accurately detects alopecia areata with 84.3% accuracy.
research An Improved Face Image Restoration Method Based on Denoising Diffusion Probabilistic Models
The new method improves facial image restoration quality and face recognition accuracy.
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 Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
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 BaldPredict: AI-Driven Prediction Model for Alopecia Areata
AI can improve alopecia areata diagnosis with high accuracy.
research Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.