AIMC Topic: Machine Learning

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Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens.

Communications biology Aug 20, 2025
Variations in host species significantly impact bacterial growth traits and antibiotic resistance, making it essential to consider host origin when evaluating the zoonotic potential of pathogens. This study focuses on multiple Brucella species, which...
Brucella Sheep Genome, Bacterial Zoonoses Cattle Animals Humans Brucellosis Swine Machine Learning Whole Genome Sequencing Genome-Wide Association Study
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Machine learning model for early diagnosis of breast cancer based on PiRNA expression with CA153.

Scientific reports Aug 20, 2025
PIWI-interacting RNAs (piRNAs) have been implicated in the biological processes of various cancers. This study aimed to investigate the diagnostic potential of circulating piRNAs in breast cancer (BC) using machine learning (ML) frameworks. A serum t...
Algorithms Female Adult Breast Neoplasms Biomarkers, Tumor Middle Aged Humans Machine Learning Gene Expression Regulation, Neoplastic Early Detection of Cancer RNA, Small Interfering Piwi-Interacting RNA
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Personalized blood glucose prediction in type 1 diabetes using meta-learning with bidirectional long short term memory-transformer hybrid model.

Scientific reports Aug 20, 2025
Personalized blood glucose (BG) prediction in Type 1 Diabetes (T1D) is challenged by significant inter-patient heterogeneity. To address this, we propose BiT-MAML, a hybrid model combining a Bidirectional LSTM-Transformer with Model-Agnostic Meta-Lea...
Precision Medicine Humans Long Short Term Memory Machine Learning Female Blood Glucose Male Diabetes Mellitus, Type 1
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Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning.

Scientific reports Aug 20, 2025
Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. In this study, we applied various machine learning techniques to predict bacter...
Bacteria Phenotype Microbial Sensitivity Tests Genotype Machine Learning Anti-Bacterial Agents Drug Resistance, Bacterial Humans
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Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study.

Scientific reports Aug 20, 2025
Cerebral-cardiac syndrome (CCS) is a severe cardiac complication following acute ischemic stroke, often associated with adverse outcomes. This study developed and validated a machine learning (ML) model to predict CCS using clinical, laboratory, and ...
Risk Assessment Logistic Models Support Vector Machine Aged Male Middle Aged Stroke Humans Machine Learning Retrospective Studies Female Risk Factors
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Precise and dexterous robotic manipulation via human-in-the-loop reinforcement learning.

Science robotics Aug 20, 2025
Robotic manipulation remains one of the most difficult challenges in robotics, with approaches ranging from classical model-based control to modern imitation learning. Although these methods have enabled substantial progress, they often require exten...
Algorithms Robotics Equipment Design Humans Machine Learning Reinforcement, Psychology
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Integrative machine learning and RT-qPCR analysis identify key stress-responsive genes in Thermus thermophilus HB8.

Genetica Aug 20, 2025
Bacteria are constantly exposed to diverse environmental stresses, necessitating complex adaptive mechanisms for survival. Thermus thermophilus, a thermophilic extremophile, serves as an excellent model for investigating these responses due to its re...
Bacterial Proteins Gene Expression Profiling Stress, Physiological Machine Learning Transcriptome Gene Expression Regulation, Bacterial Thermus thermophilus Phylogeny Real-Time Polymerase Chain Reaction
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Symptom Recognition in Medical Conversations Via multi- Instance Learning and Prompt.

Journal of medical systems Aug 20, 2025
With the widespread adoption of electronic health record (EHR) systems, there is a crucial need for automatic extraction of key symptom information from medical dialogue to support intelligent medical record generation. However, symptom recognition i...
Symptom Assessment Electronic Health Records Humans Communication Machine Learning Natural Language Processing
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The prediction models for the optimal timing of surgical intervention for necrotizing enterocolitis: nomogram vs. five machine learning models.

Pediatric surgery international Aug 20, 2025
BACKGROUND: Necrotizing enterocolitis (NEC) is one of the most common diseases that pose serious threats to the life of newborns. In clinical practice, NEC is typically treated by surgical intervention, but it is still difficult to identify the timin...
Humans Machine Learning Male Nomograms Time-to-Treatment Enterocolitis, Necrotizing Retrospective Studies Female Infant, Newborn
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Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.

Alzheimer's research & therapy Aug 20, 2025
BACKGROUND AND OBJECTIVES: Early and cost-effective identification of amyloid positivity is crucial for Alzheimer's disease (AD) diagnosis. While amyloid PET is the gold standard, plasma biomarkers such as phosphorylated tau 217 (pTau217) provide a p...
Male tau Proteins Female Middle Aged Positron-Emission Tomography Humans Amyloid beta-Peptides Peptide Fragments Aged Cost-Benefit Analysis Machine Learning Aged, 80 and over Glial Fibrillary Acidic Protein Neurofilament Proteins Biomarkers Alzheimer Disease
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