AIMC Topic: Machine Learning

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Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Scientific reports Jun 5, 2025
Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the proneural subtype has a relatively good prognosis, and the mesenchymal type is the most aggressive form with the worst prognosis. GBM undergoes proneura...
Tumor Microenvironment Biomarkers, Tumor Brain Neoplasms Gene Expression Profiling Humans Proteomics Transcriptome Machine Learning Glioblastoma Epithelial-Mesenchymal Transition Gene Regulatory Networks Multiomics Prognosis Gene Expression Regulation, Neoplastic
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Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

Scientific reports Jun 5, 2025
The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for ...
Anti-Bacterial Agents Drug Resistance, Bacterial Aged Cross Infection Pseudomonas aeruginosa Pseudomonas Infections Carbapenems Boosting Machine Learning Algorithms Adult Male Humans Machine Learning Female Risk Factors Middle Aged ROC Curve
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer.

Scientific reports Jun 5, 2025
Breast cancer is the most common type of cancer in women, and while current treatments can cure the majority of early-stage primary BC cases, recurrence remains a significant challenge. Traditional methods of assessing patient prognosis, such as AJCC...
Prognosis Female Breast Neoplasms Gene Expression Profiling Transcriptome Tumor Microenvironment Biomarkers, Tumor Humans Machine Learning Algorithms Gene Expression Regulation, Neoplastic Neoplasm Recurrence, Local
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Harnessing vaginal inflammation and microbiome: a machine learning model for predicting IVF success.

NPJ biofilms and microbiomes Jun 5, 2025
Humans are the only species with a commensal Lactobacillus-dominant vaginal microbiota. Reproductive tract microbes have been linked to fertility outcomes, as has intrauterine inflammation, suggesting immune response may mediate adverse outcomes. In ...
Male Pilot Projects Fertilization in Vitro Microbiota Vagina Machine Learning Pregnancy Outcome Pregnancy Inflammation Female Adult Humans
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Ensemble of weak spectral total-variation learners: a PET-CT case study.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jun 5, 2025
Solving computer vision problems through machine learning, one often encounters lack of sufficient training data. To mitigate this, we propose the use of ensembles of weak learners based on spectral total-variation (STV) features (Gilboa G. 2014 A to...
Machine Learning Algorithms Positron Emission Tomography Computed Tomography Humans
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Designing diverse and high-performance proteins with a large language model in the loop.

PLoS computational biology Jun 5, 2025
We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse...
Neural Networks, Computer Proteins Mutation Protein Engineering Large Language Models Machine Learning Algorithms Computational Biology
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Machine learning-based prediction model for cognitive impairment risk in patients with chronic kidney disease.

PloS one Jun 5, 2025
BACKGROUND: The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.
Longitudinal Studies Logistic Models Renal Insufficiency, Chronic Support Vector Machine Algorithms China Humans Prognosis Cognitive Dysfunction Neural Networks, Computer Female Middle Aged Machine Learning Risk Assessment Risk Factors Aged Male
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Identifying dynamic regulation with machine learning using adversarial surrogates.

PloS one Jun 5, 2025
Biological systems maintain stability of their function in spite of external and internal perturbations. An important challenge in studying biological regulation is to identify the control objectives based on empirical data. Very often these objectiv...
Humans Machine Learning Algorithms Computer Simulation Models, Biological
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Recognition of flight cadets brain functional magnetic resonance imaging data based on machine learning analysis.

PloS one Jun 5, 2025
The rapid advancement of the civil aviation industry has attracted significant attention to research on pilots. However, the brain changes experienced by flight cadets following their training remain, to some extent, an unexplored territory compared ...
Machine Learning Brain Female Young Adult Humans Aviation Magnetic Resonance Imaging Brain Mapping Bayes Theorem Pilots Adult Male Support Vector Machine
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A descriptor-free machine learning framework to improve antigen discovery for bacterial pathogens.

PloS one Jun 5, 2025
Identifying protective antigens (PAs), i.e., targets for bacterial vaccines, is challenging as conducting in-vivo tests at the proteome scale is impractical. Reverse Vaccinology (RV) aids in narrowing down the pool of candidates through computational...
Bacterial Vaccines Vaccinology Neural Networks, Computer Machine Learning Computational Biology Antigens, Bacterial Software Bacteria
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