research Collider bias undermines our understanding of COVID-19 disease risk and severity
Collider bias can distort our understanding of COVID-19 risk and severity.
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research Comparative Analysis of Machine Learning Algorithms in Diagnosis of Polycystic Ovarian Syndrome
The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.
research ISID0197 - Quantitative analysis of hair loss in mice utilizing imageJ improves the efficacy evaluation of alopecia areata induction in the C3H/HeJ mouse model
A new image-based method improves accuracy in measuring hair loss in mice.
research Clinically relevant skull models and optical measurement method to evaluate programmable hydrocephalus valve tool kit usability
Three skull models were found most useful for testing hydrocephalus valve programming.
research A Simple Decision Tree Suited for Identification of Early Oral Drug Candidates With Likely Pharmacokinetic Nonlinearity by Intestinal CYP3A Saturation
The decision tree can predict drug absorption issues with good accuracy but needs more validation and adjustments for other factors.
research Integrating Biomarkers from Correlation Analysis and Metric Learning for Hair Loss Classification
Combining biomarker analysis and advanced algorithms improves hair loss detection accuracy.
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 Optimization of finasteride nano-emulsion preparation by using chemometrics approaches (and/or Box-Behnken design and regresion model)
research Integrated edge information and pathway topology for drug-disease associations
iEdgePathDDA effectively finds new drug-disease links, outperforming other methods.
research GBP1 as a machine learning-prioritized biomarker and therapeutic target for epstein-barr virus-induced clear cell renal cell carcinoma: multi-omics causal validation
GBP1 is a key target for treating Epstein-Barr virus-related kidney cancer, and finasteride may help.
research The inheritance of common baldness: Two B or not two B ?
Common baldness is likely inherited through multiple genes, not just one.
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 A Critical Evaluation of Evaluations for Long-form Question Answering
Current methods can't accurately predict which long-form answers people prefer; evaluations should consider different answer qualities separately.
research Analysis of the human diseasome using phenotype similarity between common, genetic and infectious diseases
The study found that diseases can be grouped by symptoms and that the accuracy of predicting disease-related genes varies with the data source.
research Mathematical Modeling of Alopecia Areata: Unraveling Hair Cycle Dynamics, Disease Progression, and Treatment Strategies
The model helps understand alopecia areata and suggests treatment strategies.
research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.2)"
The study improved and was accepted despite initial concerns about data clarity, methodology, and potential overfitting.
research Genetic Prediction of Eye, Hair, and Skin Color: Forensic Applications and Challenges in Latin American Populations
Accurate prediction of eye, hair, and skin color in Latin American populations requires region-specific models and ethical guidelines.
research Using a capture–recapture method to assess the frequency of adverse drug reactions in a French university hospital
The study found that combining different databases gives a better estimate of drug side effects in hospitals.
research 197 Quantitative analysis of hair loss in mice utilizing imageJ improves the efficacy evaluation of alopecia areata induction in the C3H/HeJ mouse model
A new image-based method improves accuracy in measuring hair loss in mice.
research A guide for building biological pathways along with two case studies: hair and breast development
The document explains how to create detailed biological pathways using genomic data and tools, with examples of hair and breast development.
research Reconstructing temporal variation in great ape and other primate diets: A methodological framework for isotope analyses in hair
Stable isotope analysis of hair helps study primate diets over time non-invasively.
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 Trends and techniques: a statistical review of hair care product evaluation research
Better standardization and transparency in statistical reporting are needed to improve hair care research quality.
research Hair analysis based on medical history and spatial-temporal data
Machine learning can predict hair health accurately using personal data.
research Optimization and validation of spectrophotometric methods for determination of finasteride in dosage and biological forms
The methods accurately measure finasteride in different forms.
research Molecular Morbidity Score–Can MicroRNAs Assess the Burden of Disease?
MicroRNAs could help assess and manage multiple chronic diseases.
research Congress abstracts SPEDM
The Bethesda system is effective for identifying thyroid cancer but has low sensitivity.
research Patient Validation of Estimation of Health Utility Values in Alopecia Areata
Patients with Alopecia Areata are willing to trade life duration for better quality of life.
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 Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases
The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.