AIMC Topic: Machine Learning

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Integrating machine learning and structural dynamics to explore B-cell lymphoma-2 inhibitors for chronic lymphocytic leukemia therapy.

Molecular diversity Jan 9, 2025
Chronic lymphocytic leukemia (CLL) is a malignancy caused by the overexpression of the anti-apoptotic protein B-cell lymphoma-2 (BCL-2), making it a critical therapeutic target. This study integrates computational screening, molecular docking, and mo...
Antineoplastic Agents Protein Binding Molecular Dynamics Simulation Proto-Oncogene Proteins c-bcl-2 Humans Machine Learning Leukemia, Lymphocytic, Chronic, B-Cell Molecular Docking Simulation
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Machine learning techniques to predict diabetic ketoacidosis and HbA1c above 7% among individuals with type 1 diabetes - A large multi-centre study in Australia and New Zealand.

Nutrition, metabolism, and cardiovascular diseases : NMCD Jan 9, 2025
BACKGROUND AND AIMS: Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.
Young Adult Adult Male Middle Aged Prognosis Female Risk Factors Diabetic Ketoacidosis Support Vector Machine Australia Predictive Value of Tests Risk Assessment Deep Learning Adolescent Diabetes Mellitus, Type 1 Humans Machine Learning Decision Support Techniques Prospective Studies Biomarkers Glycated Hemoglobin New Zealand
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Machine Learning Algorithms in Controlled Donation After Circulatory Death Under Normothermic Regional Perfusion: A Graft Survival Prediction Model.

Transplantation Jan 9, 2025
BACKGROUND: Several scores have been developed to stratify the risk of graft loss in controlled donation after circulatory death (cDCD). However, their performance is unsatisfactory in the Spanish population, where most cDCD livers are recovered usin...
Predictive Value of Tests Liver Transplantation Perfusion Spain Tissue Donors Graft Survival Treatment Outcome Machine Learning Female Humans Algorithms Male Risk Factors Decision Support Techniques Middle Aged Aged Retrospective Studies Risk Assessment Adult Time Factors
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Machine Learning Approach for Sepsis Risk Assessment in Ischemic Stroke Patients.

Journal of intensive care medicine Jan 9, 2025
BackgroundIschemic stroke is a critical neurological condition, with infection representing a significant aspect of its clinical management. Sepsis, a life-threatening organ dysfunction resulting from infection, is among the most dangerous complicati...
Logistic Models Ischemic Stroke Male Middle Aged Risk Assessment Sepsis Intensive Care Units Female Aged Humans Machine Learning
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Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma.

Academic radiology Jan 9, 2025
RATIONALE AND OBJECTIVES: To develop and externally validate interpretable CT radiomics-based machine learning (ML) models for preoperative Ki-67 expression prediction in clear cell renal cell carcinoma (ccRCC).
Kidney Neoplasms Carcinoma, Renal Cell Ki-67 Antigen Radiomics Humans Male Machine Learning Middle Aged Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Female Aged Adult
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Contrastive Graph Representation Learning with Adversarial Cross-View Reconstruction and Information Bottleneck.

Neural networks : the official journal of the International Neural Network Society Jan 9, 2025
Graph Neural Networks (GNNs) have received extensive research attention due to their powerful information aggregation capabilities. Despite the success of GNNs, most of them suffer from the popularity bias issue in a graph caused by a small number of...
Algorithms Humans Neural Networks, Computer Machine Learning
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Applying artificial intelligence to uncover the genetic landscape of coagulation factors.

Journal of thrombosis and haemostasis : JTH Jan 9, 2025
Artificial intelligence (AI) is rapidly advancing our ability to identify and interpret genetic variants associated with coagulation factor deficiencies. This review introduces AI, with a specific focus on machine learning (ML) methods, and examines ...
Hemophilia A Phenotype Humans Blood Coagulation Genetic Predisposition to Disease Mutation Artificial Intelligence Genetic Association Studies Genetic Variation Machine Learning Blood Coagulation Factors
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Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting.

Sleep health Jan 9, 2025
GOAL AND AIMS: One challenge using wearable sensors is nonwear time. Without a nonwear (e.g., capacitive) sensor, actigraphy data quality can be biased by subjective determinations confounding sleep/wake classification. We developed and evaluated a m...
Algorithms Female Adult Male Humans Middle Aged Machine Learning Wearable Electronic Devices Sleep Actigraphy
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Machine learning models provide modest accuracy in predicting clinical impact of porcine reproductive and respiratory syndrome type 2 in Canadian sow herds.

American journal of veterinary research Jan 9, 2025
OBJECTIVE: To determine the predictive potential of the open reading frame 5 nucleotide sequence of porcine reproductive and respiratory syndrome (PRRS) virus and the basic demographic data on the severity of the impact on selected production paramet...
Machine Learning Retrospective Studies Female Animals Longitudinal Studies Porcine Reproductive and Respiratory Syndrome Porcine respiratory and reproductive syndrome virus Disease Outbreaks Swine Ontario
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Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.

Drug safety Jan 9, 2025
BACKGROUND: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence ...
Machine Learning Electronic Health Records Natural Language Processing Humans Drug-Related Side Effects and Adverse Reactions Pharmacovigilance Adverse Drug Reaction Reporting Systems
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