AIMC Topic: Machine Learning

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Optimization of hemocompatibility metrics in ventricular assist device design using machine learning and CFD-based response surface analysis.

The International journal of artificial organs Jun 6, 2025
Ventricular assist devices (VADs) are essential for end-stage heart failure patients, but their design must balance hydraulic efficiency and hemocompatibility to minimize blood damage. This study presents a multi-objective optimization framework inte...
Stress, Mechanical Hemolysis Models, Cardiovascular Platelet Activation Hydrodynamics Heart Failure Materials Testing Heart-Assist Devices Bayes Theorem Prosthesis Design Humans Machine Learning Computer Simulation
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Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.

PloS one Jun 6, 2025
Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct human-caused historical long-distance seed transfer and to spot mislabelling in forest field trials....
Trees Fagus Humans Polymorphism, Single Nucleotide Europe Machine Learning Quercus Forests
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An efficient low-shot class-agnostic counting framework with hybrid encoder and iterative exemplar feature learning.

PloS one Jun 6, 2025
Few-shot learning techniques have enabled the rapid adaptation of a general AI model to various tasks using limited data. In this study, we focus on class-agnostic low-shot object counting, a challenging problem that aims to achieve accurate object c...
Algorithms Image Processing, Computer-Assisted Humans Machine Learning
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MTSA-SC: A multi-task learning approach for individual trip destination prediction with multi-trajectory subsequence alignment and space-aware loss functions.

PloS one Jun 6, 2025
Individual Trip Destination Prediction aims to accurately forecast an individual's future travel destinations by analyzing their historical trajectory data, holding significant application value in intelligent navigation, personalized recommendations...
Humans Machine Learning Algorithms Forecasting Travel
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Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches.

Ecotoxicology and environmental safety Jun 5, 2025
BACKGROUND: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abnormal glucose metabolism, particularly type 2 diabetes. Hyperglycemia can increase the formation of a...
Machine Learning Biomarkers Female Humans Metals Nutrition Surveys Aged Male Glucose Adult Middle Aged Sarcopenia Diabetes Mellitus, Type 2
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Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China.

Ecotoxicology and environmental safety Jun 5, 2025
Soil heavy metal contamination poses serious health risks, but few studies have quantitatively assessed disparities in these risks between urban and rural populations. To address this gap, we introduce a novel framework integrating machine learning a...
Risk Assessment China Rural Population Machine Learning Soil Humans Soil Pollutants Urban Population Environmental Exposure Environmental Monitoring Metals, Heavy
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MFDSMC: Accurate Identification of Cancer-Driver Synonymous Mutations Using Multiperspective Feature Representation Learning.

Journal of chemical information and modeling Jun 5, 2025
Synonymous mutations do not change amino acid sequences, but they can drive cancer by influencing splicing, mRNA structure, translation efficiency, and other molecular mechanisms. Although driver synonymous mutations are significantly outnumbered by ...
Silent Mutation Neoplasms Humans Computational Biology Machine Learning Mutation
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MlCOFSyn: A Machine Learning Framework To Facilitate the Synthesis of 2D Covalent Organic Frameworks.

Journal of chemical information and modeling Jun 5, 2025
Two-dimensional covalent organic frameworks (2D COFs) have been historically synthesized empirically, often resulting in uncontrolled crystallization and inferior crystal sizes, which limit their performance in various applications. Recently, crystal...
Chemistry Techniques, Synthetic Machine Learning Metal-Organic Frameworks Crystallization Models, Molecular
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Machine Learning Based Quantitative Structure-Dissolution Profile Relationship.

Journal of chemical information and modeling Jun 5, 2025
Determining accurate drug dissolution processes in the gastrointestinal tract is critical in drug discovery as dissolution profiles provide essential information for estimating the bioavailability of orally administered drugs. While various methods h...
Solubility Sodium Dodecyl Sulfate Quantitative Structure-Activity Relationship Machine Learning Surface-Active Agents Pharmaceutical Preparations Neural Networks, Computer
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scGANSL: Graph Attention Network with Subspace Learning for scRNA-seq Data Clustering.

Journal of chemical information and modeling Jun 5, 2025
Single-cell RNA sequencing (scRNA-seq) has become a crucial technology for analyzing cellular diversity at the single-cell level. Cell clustering is crucial in scRNA-seq data analysis as it accurately identifies distinct cell types and uncovers poten...
Single-Cell Gene Expression Analysis Sequence Analysis, RNA Cluster Analysis Single-Cell Analysis RNA-Seq Principal Component Analysis Humans Machine Learning
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