research Xgboost Algoritmasıyla Polikistik Over Sendromu Teşhisi
XGBoost can effectively diagnose PCOS with 87% accuracy.
Search
for
Sort by
Research
30 / 1000+ results
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.
research Early prediction of alopecia areata using machine learning modeling of neuro stress immune signatures from multi datasets
A machine learning model can predict alopecia areata early using specific gene markers.
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 Prediction of therapeutic outcomes of female pattern hair loss patients based on clinical features with application of artificial intelligence
Artificial intelligence can accurately predict hair growth and treatment results in female pattern hair loss patients, with age of onset and duration being key factors.
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 Predicting Polycystic Ovary Syndrome among Reproductive-Aged Women in Bangladesh Using Machine Learning Algorithms: Development of a Hospital-Based Predictive Model
Machine learning can accurately predict Polycystic Ovary Syndrome in women using clinical features.
research AI04 A novel machine learning software application for prognosticating cutaneous malignant melanoma based on data from 78 351 patients from the Surveillance, Epidemiology, and End Results (SEER) database
The new AI software predicts melanoma outcomes more accurately than traditional methods.
research Predictive Modeling of Hair Fall using Random Forest Algorithms
The model accurately predicts hair loss by analyzing various factors.
research Drug Repurposing against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study
Afatinib, neratinib, and zanubrutinib could be effective against KRASG12C-mutant tumors.
research A Comparative Study of Machine Learning Algorithms in Predicting Mental Disorders
Machine learning can accurately predict mental disorders.
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 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.
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 Smart Diagnostic System for Health Risk Assessment
WomenCare helps predict PCOD risk in women to encourage early medical consultation.
research Comparison of Linear Regression, Decision Tree Regression, and Random Forest Regression Algorithms in Predicting Baldness Risk
Random Forest Regression is best for predicting baldness risk.
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 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 A machine learning and network framework to discover new indications for small molecules
A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
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 Performance exploration of multi-gene panels of alopecia areata susceptibility and drug-binding targets
Methotrexate, resveratrol, and curcumin may help treat alopecia areata by targeting immune cells.
research Invited Speaker Abstracts
Technological advancements and standardization are crucial for improving diagnostic accuracy and laboratory efficiency.
research Understanding Polycystic Ovary Syndrome
PCOS affects women's hormones and metabolism, but can be managed with lifestyle changes and treatments.
research Sparse haplotype-based fine-scale local ancestry inference at scale reveals recent selection on immune responses
Recent selection on immune response genes was identified across seven ethnicities.
research ANAIS DO I CONGRESSO MÉDICO DE FORMOSA - COMEF
Dutasteride is more effective and better tolerated than finasteride for hair loss treatment.
research Aspect-Level Drug Reviews Sentiment Analysis Based on Double BiGRU and Knowledge Transfer
A model called PM-DBiGRU was developed for analyzing sentiments in drug reviews, and it performed better than other models, but struggled with complex sentences and situations requiring background knowledge.
research An Explainable AI-Based Decision Support System for Teaching and Classifying Hair Loss Types
The AI system accurately classifies hair loss types and explains its decisions.
research Novel topical booster enhances follicular sulfotransferase activity in patients with androgenetic alopecia: a new strategy to improve minoxidil response
Topical booster improves hair loss treatment effectiveness.
research Comprehensive whole-genome resequencing unveils genetic diversity and selective signatures of the Xiangdong black goat
Xiangdong black goats have moderate genetic diversity, minimal inbreeding, and important genes for reproduction, immunity, and other traits.
research Big Self-Supervised Models Advance Medical Image Classification
Self-supervised learning improves medical image classification accuracy.