AIMC Topic: Humans

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A convenient machine learning model to predict full stomach and evaluate the safety and comfort improvements of preoperative oral carbohydrate in patients undergoing elective painless gastrointestinal endoscopy.

Annals of medicine
BACKGROUND AND AIMS: Assessment of the patient's gastric contents is the key to avoiding aspiration incidents, however, there is no effective method to determine whether elective painless gastrointestinal endoscopy (GIE) patients have a full stomach ...

A machine learning approach for the classification of sports based on a coaches' perspective of environmental, individual and task requirements: A sports profile analysis.

Journal of sports sciences
Well-designed talent programmes in sports with a focus on talent identification, orientation, development, and transfer support the engagement of young individuals and the pursuit of elite performance. To facilitate these processes, an analysis of ta...

Early-stage neutralizing antibody level associated with the re-positive risk of Omicron SARS-CoV-2 RNA in patients recovered from COVID-19.

Diagnostic microbiology and infectious disease
Post-discharge re-positivity of Omicron SARS-CoV-2 is challenging for the sufficient control of this pandemic. However, there are few studies about the risk of re-positivity. We aimed to explore the association of neutralizing antibodies (nAbs, AU/mL...

A Stepwise Approach to Analyzing Musculoskeletal Imaging Data With Artificial Intelligence.

Arthritis care & research
The digitization of medical records and expanding electronic health records has created an era of "Big Data" with an abundance of available information ranging from clinical notes to imaging studies. In the field of rheumatology, medical imaging is u...

Comparison Results of Three-Port Robot-Assisted and Uniportal Video-Assisted Lobectomy for Functional Recovery Index in the Treatment of Early Stage Non-small Cell Lung Cancer: A Propensity Score-Matched Analysis.

Annals of surgical oncology
BACKGROUND: Minimally invasive lobectomy is the standard treatment for early stage non-small cell lung cancer (NSCLC). The aim of this study is to investigate postoperative recovery in a prospective trial of discharged patients with early stage non-s...

Expanding from unilateral to bilateral: A robust deep learning-based approach for predicting radiographic osteoarthritis progression.

Osteoarthritis and cartilage
OBJECTIVE: To develop and validate a deep learning (DL) model for predicting osteoarthritis (OA) progression based on bilateral knee joint views.

Deep learning radiomics on shear wave elastography and b-mode ultrasound videos of diaphragm for weaning outcome prediction.

Medical engineering & physics
PURPOSE: We proposed an automatic method based on deep learning radiomics (DLR) on shear wave elastography (SWE) and B-mode ultrasound videos of diaphragm for two classification tasks, one for differentiation between the control and patient groups, a...

GPDRP: a multimodal framework for drug response prediction with graph transformer.

BMC bioinformatics
BACKGROUND: In the field of computational personalized medicine, drug response prediction (DRP) is a critical issue. However, existing studies often characterize drugs as strings, a representation that does not align with the natural description of m...

Identifying multi-target drugs for prostate cancer using machine learning-assisted transcriptomic analysis.

Journal of biomolecular structure & dynamics
Prostate cancer is a leading cause of cancer death in men, and the development of effective treatments is of great importance. This study explored to identify the candidate drugs for prostate cancer by transcriptomic data and CMap database analysis. ...