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research DrugNet: Network-based drug–disease prioritization by integrating heterogeneous data
DrugNet effectively identifies new uses for existing drugs and may save resources in drug development.
research The Relative Efficacy and Safety of Therapies for Alopecia Areata: Protocol for a Network Meta-Analysis Study
research Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguation
Fine-tuned BERT models are better than LLMs for detecting bias in medical data.
research A machine learning and network framework to discover new indications for small molecules
The model successfully predicted new uses for existing drugs, like using certain hormonal and heart medications for respiratory and Parkinson's diseases, and a cancer drug for diabetes.
research Group-ICA Model Order Highlights Patterns of Functional Brain Connectivity
Choosing the right model order in brain connectivity analysis can affect the detection of differences between healthy individuals and those with seasonal affective disorder.
research The comparative effect of monotherapies for male androgenetic alopecia: a protocol for network meta-analysis study
The document aims to compare the effectiveness of different single treatments for male pattern hair loss.
research A weighted non-negative matrix factorization approach to predict potential associations between drug and disease
WNMFDDA effectively predicts drug-disease associations.
research PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models
PROMETHEUS helps organize and evaluate causal claims from large language models.
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 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 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 DEEP REINFORCEMENT LEARNING FOR SCALABLE CONTROL OF BOOLEAN MODELS IN THE CONTEXT OF CELLULAR REPROGRAMMING
pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
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 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 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.
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 Relative efficacy of minoxidil and 5-alpha-reductase inhibitors in the treatment of male androgenetic alopecia: protocol for a network meta-analysis study
research The temptation of large numbers
Large databases in research can lead to misleading conclusions due to biases and chance findings; researchers should analyze data more rigorously.
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 Empirical evidence of observer bias in randomized clinical trials: updated and expanded analysis of trials with both blinded and non-blinded outcome assessors
Non-blinded assessors tend to overestimate effects in trials by about 29%.
research Genetic prediction of male pattern baldness based on large independent datasets
New models predict male pattern baldness better than old ones but still need improvement.
research Community Detection and Patient Experience Analysis in Reddit Conversations on Janus Kinase Inhibitors using Large Language Models
A few users dominate Reddit discussions on JAK inhibitors, highlighting social media's potential for tracking drug safety but needing expert oversight.
research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.3)"
Reviewers criticized the study's methods and suggested focusing on drug mechanisms instead of repositioning due to social media data quality concerns.
research A Powerful Method for Pleiotropic Analysis under Composite Null Hypothesis Identifies Novel Shared Loci Between Type 2 Diabetes and Prostate Cancer
The new method found new shared genetic areas linked to both Type 2 Diabetes and Prostate Cancer.
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 Peer Review #2 of "Computational drug repositioning based on side-effects mined from social media (v0.1)"
Reviewers suggested the study on finding new drug uses through social media side-effects needs better methods and clearer limitations.
research Combination Therapies and the Theoretical Limits of Evidence-Based Medicine
The current system can't fully test all combination treatments, so alternative methods and regulatory flexibility are needed.
research Minimizing Factual Inconsistency and Hallucination in Large Language Models
A new method improves the accuracy and reliability of language models by up to 42%.
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.