research A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
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270-300 / 1000+ results research Applying Machine Learning Technique on Registry Data to Assess Factors Associated With In-Hospital Mortality Among STEMI Patients With Hypertension
Age, diabetes, and cardiogenic shock at PCI are key factors linked to in-hospital death in STEMI patients with hypertension.
research A Data-Driven Approach to Polycystic Ovary Syndrome Diagnosis: Evaluating Machine Learning Models
Machine learning can improve early and accurate detection of PCOS.
research Dodatek A: Model matematyczny AL/RC/ASE. Functional Androgen Axis (FOA) - wersja operacyjna v1.2
The model improves understanding of androgen interactions by focusing on signal intensity and system capacity.
research A Comparative Study of Machine Learning Algorithms in Predicting Mental Disorders
Machine learning can accurately predict mental disorders.
research Dodatek A: Model matematyczny AL/RC/ASE. Functional Androgen Axis (FOA) - wersja operacyjna v1.2
The model improves understanding of androgen interactions by focusing on signal intensity and system capacity.
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 Explaining and predicting the single channel versus multi-channel consumer: the case of an embarrassing product
The Theory of Planned Behaviour predicts consumer behavior better when emotions, personality, demographics, and marketing are included.
research rwSALT: a regrowth-weighted SALT score providing direct pixel-level measurement rather than visual estimation
rwSALT provides precise hair regrowth measurement from scalp photos.
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 Phenotype-Specific Lifestyle Prediction for PCOS Using Machine Learning Multi-Class Classification and SHAP Explainability
Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.
research 1451 THE ASSOCIATION BETWEEN MALE PATTERN BALDNESS AND SECOND TO FORTH FINGER RATIO WITH PROSTATE CANCER- A PROSPECTIVE COHORT STUDY
Male pattern baldness may predict prostate cancer risk.
research 원저 : 원형탈모증에 대한 스테로이드제 미니 펄스요법의 효과
Minipulse therapy with betamethasone effectively promotes hair regrowth in alopecia areata with fewer side effects.
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 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 MendelVar: gene prioritization at GWAS loci using phenotypic enrichment of Mendelian disease genes
MendelVar is a tool that helps identify important genes by combining GWAS data with Mendelian disease information.
research rwSALT: a regrowth-weighted SALT score providing direct pixel-level measurement rather than visual estimation
rwSALT accurately measures hair regrowth in alopecia areata using scalp photos.
research Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits
Using trait prevalence priors in genetic prediction models for appearance traits is currently impractical due to limited knowledge and potential accuracy issues.
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 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 42063 Image Quality Assessment using Convolutional Neural Network in Clinical Skin Images
The model can effectively identify good quality skin images but needs more testing for real-world use.
research A flexible fixed-sequence testing method for hierarchically ordered correlated multiple endpoints in clinical trials
The flexible fixed-sequence testing method allows for more effective evaluation of multiple goals in a clinical trial while controlling the risk of false positives.
research 199 Hand preference and sexual orientation as useful elements to predict finasteride side effects in male androgenic alopecia
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 Select the most correct answers – multiple answers possible for questions 1–11
Medical practitioners need to understand basic statistics to properly evaluate clinical trials and avoid unethical designs.
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 원저 : Mohs 미세도식 수술을 이용한 안검부 기저세포암의 준임상적 침윤 유형에 관한 연구
Oral minipulse therapy with betamethasone effectively promotes hair regrowth in alopecia areata with fewer side effects.
research ARTIFICIAL INTELLIGENCE TECHNIQUES IN PREDICTION OF COVID-19 MORTALITY AND ITS RELATED FACTORS: A MULTI-CENTER STUDY
AI can effectively predict COVID-19 mortality risk using patient data.
research ANTHROPOMETRIC ASSESSMENT OF DIGIT LENGTHS AND DIGIT RATIOS OFVITILIGO SUBJECTS IN PORT HARCOURT, RIVERS STATE
Understanding the 2D:4D digit ratio in vitiligo patients may help in clinical assessments.
research Addressing continuous data for participants excluded from trial analysis: a guide for systematic reviewers
The conclusion is that the risk of losing significance in meta-analysis results increases with smaller effects and more missing data, and using the median standard deviation for imputation is recommended.