AIMC Topic: Machine Learning

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Inflammation and B cell activation define a plasma proteome signature predicting tuberculosis in people with HIV.

mBio
Improved biomarkers for predicting progression to active tuberculosis (TB) are urgently needed, especially in people with HIV, who are at elevated risk. We used high-throughput plasma proteomics and machine learning to identify signatures associated ...

Mapping a interactome by crosslinking mass spectrometry and machine learning.

mBio
, a widespread human parasite, persists in hosts through complex molecular interactions. Protein-protein interactions (PPIs) underpin essential biological processes, including parasite-host interactions and cellular invasion. Herein, we utilized adva...

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models.

Journal of chemical information and modeling
The discovery of Metal-Organic Frameworks (MOFs) with application-specific properties remains a central challenge in materials chemistry, owing to the immense size and complexity of their structural design space. Conventional computational screening ...

Machine learning in predicting preoperative intra-aortic balloon pump use in patients undergoing coronary artery bypass grafting.

Journal of cardiothoracic surgery
BACKGROUND: Intra-aortic balloon pump (IABP) implantation in the perioperative period of cardiac surgery is an auxiliary treatment for cardiogenic shock. However, there is a lack of effective prediction models for preoperative IABP implantation.

Predicting survival factor following suicide attempt in Iran: an ensemble machine learning technique.

BMC psychiatry
BACKGROUND: Suicide represents a significant challenge to public health that calls for a suitable intervention from the healthcare sector. Despite the typically low suicide rate among most Muslim nations, research indicates that there is an increase ...

Mapping interconnectivity of digital twin healthcare research themes through structural topic modeling.

Scientific reports
Digital twin (DT) technology is revolutionizing healthcare systems by leveraging real-time data integration and advanced analytics to enhance patient care, optimize clinical operations, and facilitate simulation. This study aimed to identify key rese...

A simple and effective approach for body part recognition on CT scans based on projection estimation.

Scientific reports
It is well known that machine learning models require a high amount of annotated data to obtain optimal performance. Labelling Computed Tomography (CT) data can be a particularly challenging task due to its volumetric nature and often missing and/or ...

Immune metabolic changes identify causal candidate genes and enable diagnostic frameworks in MAFLD.

Scientific reports
Metabolic dysfunction-associated fatty liver disease (MAFLD), a global epidemic affecting 25% of adults, is driven by immune-metabolic dysregulation, yet the causal mechanisms linking immune cell-specific gene perturbations to disease progression rem...

A fused weighted federated learning-based adaptive approach for early-stage drug prediction.

Scientific reports
Early accurate drug prediction is crucial in clinical decision support, where privacy of the patient data is a paramount importance. In this study, we introduce a fused weighted adaptive federated learning (FWAFL) framework to achieve joint training ...

Fire risk to structures in California's Wildland-Urban Interface.

Nature communications
The destructive impacts of wildfires on people, property and the environment have dramatically increased, especially in the Wildland-Urban Interface (WUI) in California. In these areas structures are threatened by both approaching flames and lofted e...