AIMC Topic: Machine Learning

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Large Language Model Synergy for Ensemble Learning in Medical Question Answering: Design and Evaluation Study.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, including medical question-answering (QA). However, individual LLMs often exhibit varying performance across different medical QA...

Robustness evaluation against corruptions for Optical Diffraction Tomography-based classifiers.

Computers in biology and medicine
Optical Diffraction Tomography (ODT) is a promising technique for three-dimensional imaging, but practical use demands rigorous robustness testing due to real-world noise factors. Despite the growing importance of machine learning safety, robustness ...

CoBdock-2: enhancing blind docking performance through hybrid feature selection combining ensemble and multimodel feature selection approaches.

Journal of computer-aided molecular design
Identifying orthosteric binding sites and predicting small molecule affinities remains a key challenge in virtual screening. While blind docking explores the entire protein surface, its precision is hindered by the vast search space. Cavity detection...

Comparative machine learning analysis for predicting organ tropism in breast cancer and identifying key gene signatures.

Computers in biology and medicine
BACKGROUND: Breast cancer metastasis (BCM) metastasizes preferentially to certain organs. Important genetic markers can be used for early detection and treatment. Machine learning (ML) can efficiently handle gene expression data to enhance metastasis...

The role of artificial intelligence for dengue prevention, control, and management: A technical narrative review.

Acta tropica
Dengue fever remains a significant global health threat, particularly in tropical and subtropical regions, where rapid urbanization and climate variability exacerbate its spread. Traditional surveillance and control systems often struggle with delaye...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

Scientific reports
An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms remain unclear. This study integrates epidemiological and bioinformatics approaches to investigate thei...

Development and validation of a machine learning-based nomogram for survival prediction of patients with hilar cholangiocarcinoma after curative-intent resection.

Scientific reports
Hilar cholangiocarcinoma (hCCA), a rare cancer of the biliary system, has a poor prognosis. This study aimed to investigate the risk factors affecting the survival of patients with hCCA after curative-intent resection and establish a survival predict...

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Scientific reports
Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the general population, significantly affecting morbidity and mortality. However, existing predictive models often lack sufficient accuracy and interpretability...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Scientific reports
Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcomes. We performed an integrative analysis of multi-omics data from 274 CRC patients to investigate the impact of gut microbiota composition on prognosi...