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.
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540-570 / 1000+ results research Forensic DNA phenotyping: a review on SNP panels, genotyping techniques, and prediction models
Forensic DNA phenotyping faces challenges like inconsistent terms and limited genetic knowledge.
research 199 Hand preference and sexual orientation as useful elements to predict finasteride side effects in male androgenic alopecia
research Forensic DNA Phenotyping
Forensic DNA Phenotyping accurately predicts physical traits and is used in investigations, but needs more diverse population data for confirmation.
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 Study design for the Stanford Dermatology Personal Genomics Project
The project aimed to understand how genetic test results affect patients' actions and feelings in dermatology.
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 Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Drug repurposing can speed up and reduce costs in drug discovery, especially for cancer treatment.
research Detecting shortcut learning for fair medical AI using shortcut testing
The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.
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 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 Forensic DNA Phenotyping: a review on SNP panels, genotyping techniques, and prediction models
Forensic DNA phenotyping faces challenges due to inconsistent terminology, limited genetic understanding, and debates over technology and models.
research Social Interest Data as a Proxy for Off-Label Performance-Enhancing Drug Use: Implications and Clinical Considerations
Clinicians should use social and prescription data to track trends in performance-enhancing drug use.
research Effective holistic characterization of small molecule effects using heterogeneous biological networks
Integrating biological networks improves drug repurposing and ADR prediction.
research Case-Only Trees and Random Forests for Exploring Genotype-Specific Treatment Effects in Randomized Clinical Trials with Dichotomous End Points
Case-only trees and random forests improve predictions of treatment effects in clinical trials.
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 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 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 Genetic prediction of male pattern baldness
Genetic factors can help predict male pattern baldness risk.
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 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 Utilising SNP Association Analysis as a Prospective Approach for Personalising Androgenetic Alopecia Treatment
Genetic factors could lead to personalized treatments for hair loss.
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.
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 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 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 Optimal processing for proteomic genotyping of single human hairs
The method improved hair analysis for better forensic identification.
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 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 Gleason grading controversies: what the chemoprevention trials have taught us
Finasteride reduces prostate cancer risk by 30% without affecting Gleason scores.