AIMC Topic: Humans

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Transcriptomic bioinformatics analysis proposes a novel BCL2-MAPK14-TXN oxidative stress diagnostic model of sepsis and identifies TXN as an oxidative stress-related signature gene in sepsis.

International immunopharmacology
BACKGROUND: Oxidative stress was one of key factors driving the septic development by the uncontrolled accumulation of free radicals, thus oxidative stress-related biomarkers provide a novel diagnostic option. This study focused on screening oxidativ...

A prior knowledge-supervised fusion network predicts survival after radiotherapy in patients with advanced gastric cancer.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Predicting overall survival (OS) for advanced gastric cancer patients after radiotherapy is critical for developing an individualized treatment plan. However, existing studies have focused on gastric cancer CT images with a ...

3D cardiac shape analysis with variational point cloud autoencoders for myocardial infarction prediction and virtual heart synthesis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Cardiac anatomy and physiology vary considerably across the human population. Understanding and taking into account this variability is crucial for both accurate clinical decision-making and realistic in silico modeling of cardiac function. In this w...

Performance assessment of an artificial intelligence algorithm for opportunistic screening of abdominal aortic aneurysms.

Clinical imaging
PURPOSE: Abdominal aortic aneurysm (AAA) is a common incidental finding on CT imaging performed in the acute care setting. Artificial intelligence (AI) algorithms have been developed to automatically measure aortic lumen size and thus facilitate AAA ...

Assessing large language models for acute heart failure classification and information extraction from French clinical notes.

Computers in biology and medicine
Understanding acute heart failure (AHF) remains a significant challenge, as many clinical details are recorded in unstructured text rather than structured data in electronic health records (EHRs). In this study, we explored the use of large language ...

Expert-level differentiation of incomplete Kawasaki disease and pneumonia from echocardiography via multiple large receptive attention mechanisms.

Computers in biology and medicine
BACKGROUND: Incomplete Kawasaki disease (KD) is challenging to diagnose due to its lack of classic clinical features, yet it has a higher incidence of coronary artery lesions, making early detection crucial. Echocardiography plays a vital role in ide...

BrainTract: segmentation of white matter fiber tractography and analysis of structural connectivity using hybrid convolutional neural network.

Neuroscience
Tractography uses diffusion Magnetic Resonance Imaging (dMRI) to noninvasively reconstruct brain white matter (WM) tracts, with Convolutional Neural Network (CNNs) like U-Net significantly advancing accuracy in medical image segmentation. This work p...

The application of Generative Artificial Intelligence in mental health care: A bibliometric and visualized analysis.

Asian journal of psychiatry
OBJECTIVE: Generative Artificial Intelligence (GAI) has emerged as a promising and innovative technological advancement that can increase access to mental health care services with its powerful natural language processing capabilities. Preliminary fi...

Preoperative prediction of severe short-term complications in patients with bladder cancer undergoing radical cystectomy.

Surgical oncology
BACKGROUND AND OBJECTIVE: Radical cystectomy (RC) is associated with a high risk of postoperative complications. The prediction of individual patient risk for severe complications can facilitate preoperative shared decision-making. Patients with elev...