AIMC Topic: Machine Learning

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KGRLFF: Detecting Drug-Drug Interactions Based on Knowledge Graph Representation Learning and Feature Fusion.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate prediction of drug-drug interactions (DDIs) plays an important role in improving the efficiency of drug development and ensuring the safety of combination therapy. Most existing models rely on a single source of information to predict DDIs, ...
Computational Biology Drug Interactions Humans Machine Learning Algorithms
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Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
BACKGROUND: Antimicrobial resistance is a major public health threat, and new agents are needed. Computational approaches have been proposed to reduce the cost and time needed for compound screening.
High-Throughput Screening Assays Machine Learning Caenorhabditis elegans Anti-Bacterial Agents Computational Biology Animals Methicillin-Resistant Staphylococcus aureus Microbial Sensitivity Tests Drug Evaluation, Preclinical
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Employing Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
This review article delves deeply into the various machine learning (ML) methods and algorithms employed in discerning protein functions. Each method discussed is assessed for its efficacy, limitations, potential improvements, and future prospects. W...
Machine Learning Algorithms Computational Biology Humans Proteins Databases, Protein
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Ense-i6mA: Identification of DNA N-Methyladenine Sites Using XGB-RFE Feature Selection and Ensemble Machine Learning.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
DNA N-methyladenine (6mA) is an important epigenetic modification that plays a vital role in various cellular processes. Accurate identification of the 6mA sites is fundamental to elucidate the biological functions and mechanisms of modification. How...
Algorithms Drosophila melanogaster Sequence Analysis, DNA Adenine DNA Methylation Machine Learning Animals Arabidopsis DNA Computational Biology
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Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we focus on p...
Neural Networks, Computer Machine Learning Algorithms Protein Binding Computational Biology Proteins Databases, Protein Ligands Binding Sites
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Probiotic Supplements Benefit Psoriasis Therapy Rather Than Affecting Disease Risk: Evidence from NHANES Machine-Learning and Meta-Analysis Study.

Probiotics and antimicrobial proteins Dec 9, 2024
This research aimed to evaluate the impact of probiotic supplementation on the severity of psoriasis symptoms and its association with the risk of developing the disease. We analyzed the association between probiotic usage and psoriasis among 21,942 ...
Machine Learning Female Adult Humans Nutrition Surveys Male Psoriasis Middle Aged Dietary Supplements Quality of Life Probiotics
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Predicting Early Hospital Discharge Following Revision Total Hip Arthroplasty: An Analysis of a Large National Database Using Machine Learning.

The Journal of arthroplasty Dec 9, 2024
BACKGROUND: Revision total hip arthroplasty (rTHA) was recently removed from the Medicare inpatient-only list. However, appropriate candidate selection for outpatient rTHA remains paramount. The purpose of this study was to evaluate the utility of a ...
Reoperation Aged, 80 and over Male Arthroplasty, Replacement, Hip Middle Aged Logistic Models United States Patient Discharge Humans Machine Learning Databases, Factual Retrospective Studies Female Aged
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MoMA: Momentum contrastive learning with multi-head attention-based knowledge distillation for histopathology image analysis.

Medical image analysis Dec 9, 2024
There is no doubt that advanced artificial intelligence models and high quality data are the keys to success in developing computational pathology tools. Although the overall volume of pathology data keeps increasing, a lack of quality data is a comm...
Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Humans Artificial Intelligence Machine Learning
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Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.

Medical & biological engineering & computing Dec 9, 2024
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...
Risk Assessment Arthroplasty, Replacement, Knee Reoperation Aged Male Middle Aged Humans Machine Learning Female Risk Factors
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Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Middle Aged Risk Assessment Time Factors Aged Aged, 80 and over Male Elective Surgical Procedures Random Forest Endovascular Procedures Treatment Outcome Predictive Value of Tests Aortic Aneurysm, Abdominal Humans Machine Learning Algorithms Retrospective Studies Female Risk Factors
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