research Prioritizing Susceptibility Genes for the Prognosis of Male-pattern Baldness with Transcriptome-wide Association Study
The research identified genes linked to male-pattern baldness and potential drug targets for treatment.
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600-630 / 1000+ results 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 Predictive Skin Permeation of Ethinylestradiol,α-Asarone,Finasteride and Risperidone
The Potts-Guy model best predicts skin permeability for the tested drugs.
research Prediction of male-pattern baldness from genotypes
Genetic data can predict male-pattern baldness with moderate accuracy, especially for early-onset cases in some European men.
research Generative Artificial Intelligence Tools: Evaluating Ways to Automate Your SALT ( GATEWAYS ) Scoring of Alopecia Areata
Generative AI tools can accurately score alopecia areata, reducing subjectivity in evaluations.
research Genetic prediction of male pattern baldness
Genetic factors can help predict male pattern baldness risk.
research Machine Learning Approach for Predicting Systemic Lupus Erythematosus in Oman-based Cohort
The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.
research Bayesian measurement-error-driven hidden Markov regression model for calibrating the effect of covariates on multistate outcomes: Application to androgenetic alopecia
Model improves accuracy in predicting hair loss effects.
research Generative Artificial Intelligence Tools: Evaluating Ways to Automate Your SALT (GATEWAYS) Scoring of Alopecia Areata
Generative AI tools like GPT-4o can effectively automate SALT scoring for alopecia areata, matching clinician accuracy.
research 701 Rethinking alopecia scores: Correlating measures of hair loss with established photographic scoring systems
The conclusion suggests that a new system for measuring hair loss could be created using automated analysis of photographs.
research A Segmental Approach to Scoring Hair Density from Global Images: Introducing the Scalp Coverage Scoring Method for Clinical Trials and Practice
The Scalp Coverage Scoring method reliably measures hair density from images.
research CSI on steroids
Forensic DNA phenotyping can help generate new leads in cold cases but faces accuracy, legal, and acceptance challenges.
research Are hand preference and sexual orientation possible predicting factors for finasteride adverse effects in male androgenic alopecia?
Hand preference and sexual orientation may predict finasteride side effects in male hair loss.
research Genomic Portraiture: The Science and Ethics of DNA Phenotyping in Identity Prediction
DNA phenotyping can predict physical traits like eye, hair, and skin color, improving forensic investigations.
research Analyzing Big EHR Data—Optimal Cox Regression Subsampling Procedure with Rare Events
A new method makes analyzing large datasets with rare events faster and more efficient.
research Decoding precision medicine in prediabetes: a citespace-based bibliometric analysis of current trends and future directions
Precision medicine is crucial for early diagnosis and personalized treatment in prediabetes.
research Forensic DNA phenotyping: the need for proportionate regulation and judicial clarity in law enforcement
Unified regulations and ethical guidelines are needed for fair use of forensic DNA phenotyping.
research The Use of High-Density SNP Array to Map Homozygosity in Consanguineous Families to Efficiently Identify Candidate Genes: Application to Woodhouse-Sakati Syndrome
Using SNP array testing helped quickly find the gene causing Woodhouse-Sakati syndrome in two related individuals.
research A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women
The model accurately predicts skin conditions in Korean women using genetic information, aiding personalized skincare.
research An Integrated Approach for Diabetes Detection Using Fisher Score Feature Selection and Capsule Network
The method accurately detects diabetes with 94% effectiveness, reducing misdiagnosis risk.
research Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Data-driven methods can effectively identify existing drugs for new uses, especially in cancer, infections, and respiratory diseases.
research Utilising SNP Association Analysis as a Prospective Approach for Personalising Androgenetic Alopecia Treatment
Genetic factors could lead to personalized treatments for hair loss.
research Valency based novel quantitative structure property relationship (QSPR) approach for predicting physical properties of polycyclic chemical compounds
The neighborhood face index (NFI) accurately predicts properties of complex molecules.
research Application of big data analytics in minoxidil drug development: a data-driven model for predicting efficacy and side effect risks
The model predicts minoxidil's effectiveness and side effects better than traditional methods.
research Effective holistic characterization of small molecule effects using heterogeneous biological networks
Integrating biological networks improves drug repurposing and ADR prediction.
research In Search of Predictive Models for Inhibitors of 5-alpha Reductase 2 Based on the Integration of Bioactivity and Molecular Descriptors Data.
The models can help find better inhibitors for conditions like baldness and prostate disorders.
research Evaluation of loci to predict ear morphology using two SNaPshot assays
Genetic markers can help predict ear shapes for forensic use.
research Alopecia areata predictive score: A new trichoscopy‐based tool to predict treatment outcome in patients with patchy alopecia areata
A new tool can predict hair regrowth in patchy alopecia areata patients.
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 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.