AIMC Topic: Machine Learning

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Integrating bioinformatics analysis, machine learning, and experimental validation to identify pyroptosis-related genes in the diagnosis of sepsis combined with acute liver failure.

Hereditas Aug 8, 2025
BACKGROUND: Sepsis is frequently combined with acute liver failure (ALF), a critical determinant in the mortality of septic patients. Pyroptosis is a significant form of programmed cell death that plays an important role in the inflammatory response....
Sepsis ROC Curve Mice Biomarkers Humans Animals Gene Expression Profiling Machine Learning Computational Biology Pyroptosis Liver Failure, Acute
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Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1/PD-L1: a retrospective study.

BMC medical informatics and decision making Aug 8, 2025
BACKGROUND: Anti-programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunotherapy has revolutionized cancer treatment. However, it can cause immune-related adverse events, including acute kidney injury (AKI). Such adverse e...
Acute Kidney Injury Female Aged Humans Machine Learning Retrospective Studies Neoplasms Male Immune Checkpoint Inhibitors Middle Aged Programmed Cell Death 1 Receptor Risk Assessment
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Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods.

Scientific reports Aug 8, 2025
COVID-19 has posed a significant global health challenge, affecting individuals across all age groups. While extensive research has focused on adults, pediatric patients exhibit distinct clinical characteristics that necessitate specialized predictiv...
Female SARS-CoV-2 Male Infant Severity of Illness Index Adolescent COVID-19 Algorithms Retrospective Studies Humans Machine Learning Child, Preschool Child
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Machine learning based analysis of leucocyte cell population data by Sysmex XN series hematology analyzer for the diagnosis of bacteremia.

Scientific reports Aug 8, 2025
In clinical practice, early recognition of bacteremia leads to prognostic improvement. Recently, cell population data (CPD) from the Sysmex XN-series hematology analyzer has attracted attention as a new method for the early diagnosis of bacteremia, b...
Aged, 80 and over Leukocytes Adult Leukocyte Count Male Machine Learning Middle Aged Female Bacteremia Aged Humans Neutrophils
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AAGP integrates physicochemical and compositional features for machine learning-based prediction of anti-aging peptides.

Scientific reports Aug 8, 2025
Aging is a natural phenomenon characterized by the loss of normal morphology and physiological functioning of the body, causing wrinkles on the skin, loss of hair, and compromised immune systems. Peptide therapies have emerged as a promising approach...
Aging Peptides Computational Biology Antimicrobial Peptides Humans Machine Learning Algorithms
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Breast cancer is detectable from peripheral blood using machine learning over T cell receptor repertoires.

NPJ systems biology and applications Aug 8, 2025
The immune system's defense abilities rely on the diversity of T and B lymphocytes. T Cell Receptors (TCRs) are generated through V(D)J recombination, where distinct genetic elements combine and undergo modifications, creating extensive variability. ...
Breast Neoplasms Middle Aged Receptors, Antigen, T-Cell Female Aged Adult Humans Machine Learning
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Influence of sample size and machine learning algorithms on digital soil nutrient mapping accuracy.

Environmental monitoring and assessment Aug 8, 2025
The objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, viz., multi-layer perceptron (MLP), random forest (RF), extra trees regressor (ETR), CatBoost, and gradient boost (GB), considering ...
Soil Pollutants Phosphorus Machine Learning Nitrogen Algorithms India Nutrients Soil Environmental Monitoring Sample Size
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Data quality in crowdsourcing and spamming behavior detection.

Behavior research methods Aug 8, 2025
As crowdsourcing emerges as an efficient and cost-effective method for obtaining labels for machine learning datasets, it is important to assess the quality of crowd-provided data to improve analysis performance and reduce biases in subsequent machin...
Markov Chains Data Accuracy Crowdsourcing Humans Machine Learning
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Federated hierarchical MARL for zero-shot cyber defense.

PloS one Aug 8, 2025
Cyber defense systems face increasingly sophisticated threats that rapidly evolve and exploit vulnerabilities in complex environments. Traditional approaches which often rely on centralized monitoring and static rule-based detection, struggle to adap...
Computer Security Humans Machine Learning Algorithms
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LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans.

PloS one Aug 8, 2025
Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM), lung cancer (LC), tuberculosis (TB), and COVID-19 etc. The diagnosis of LGDs is performed by using different medical imaging such as X-rays, CT sca...
Humans Neural Networks, Computer Lung Neoplasms Lung Diseases Extreme Learning Machines COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Machine Learning Pandemics
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