research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
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30 / 1000+ results research Predictive Modeling of Hair Fall using Random Forest Algorithms
The model accurately predicts hair loss by analyzing various factors.
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 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 Big Self-Supervised Models Advance Medical Image Classification
Self-supervised learning improves medical image classification accuracy.
research Transcriptomics analysis reveals molecular alterations underpinning spaceflight dermatology
Spaceflight can harm skin health by altering gene expression, affecting DNA, mitochondria, and skin barriers.
research Androgen Signaling Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men
Male hormones affect COVID-19 severity and certain drugs targeting these hormones could help reduce the risk.
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 Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programs
Long-COVID causes more health issues after COVID-19, varying by age, sex, and infection wave.
research A genetically informed brain atlas for enhancing brain imaging genomics
GIANT improves brain imaging by using genetics to better map brain regions.
research AB-MTEDeep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata
The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
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 Deep Insight of Design, Mechanism, and Cancer Theranostic Strategy of Nanozymes
Nanozymes show promise for effective and safe cancer treatment.
research AI-driven biomaterial design: an intelligent closed loop from reverse design to biological response
AI improves biomaterial design by making it faster, cheaper, and more effective for personalized medicine.
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 DiZyme: The Ultimate Resource for Nanozyme Multiple Catalytic Activity Prediction
DiZyme accurately predicts nanozyme activities to aid in discovering new applications.
research De Novo Design of Anti-Aging Peptides
New peptides can delay aging and improve cell function.
research Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguation
Fine-tuned BERT models are better than LLMs for detecting bias in medical data.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research AI06 ALUDWIG: an automated artificial intelligence-based assessment of female androgenic alopecia
ALUDWIG can help standardize female hair loss assessment from a single image.
research An Early Hair Loss Detection and Prediction Method Based on Machine Learning
Machine learning can accurately predict hair loss early, improving treatment options.
research Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Agglomerative clustering-based drugs graded for the risk signals of drug-induced cognitive disorder: a study on the FAERS database
Finasteride is high-risk for cognitive disorders, while Carbidopa/Levodopa, Topiramate, and Clonazepam are moderate-risk.
research Nano-Enabled CRISPR-Cas Gene Editing for Cancer Therapeutics
Nanotechnology improves CRISPR-Cas9 delivery for cancer treatment, but challenges remain.
research Machine Learning--Enhanced Pharmacovigilance Assessment of Cardiac Adverse Events Associated With Minoxidil
Minoxidil is strongly linked to heart problems, and machine learning can improve drug safety checks.
research Prediction of cell states and key transcription factors of the human cornea through integrated single-cell omics analyses
A new tool accurately identifies human cornea cell states and key factors.
research A Fuzzy Logic-Based Computational Framework for Precision Triage in Androgenetic Alopecia: A Simulated Biomarker-Driven Approach
The TPAP method effectively categorizes androgenetic alopecia patients with high accuracy, but needs real-world validation.
research Microbial dysbiosis and its diagnostic potential in androgenetic alopecia: insights from multi-kingdom sequencing and machine learning
Microbial imbalances on the scalp can help diagnose and manage hair loss early.
research HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
"HairSentinel" accurately detects hairfall trends using simple user data, helping identify health risks early.