AIMC Topic: Adult

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Identifying the risk of exercises, recommended by an artificial intelligence for patients with musculoskeletal disorders.

Scientific reports
Musculoskeletal disorders (MSDs) impact people globally, cause occupational illness and reduce productivity. Exercise therapy is the gold standard treatment for MSDs and can be provided by physiotherapists and/or also via mobile apps. Apart from the ...

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

Anais da Academia Brasileira de Ciencias
The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This ...

Driver drowsiness is associated with altered facial thermal patterns: Machine learning insights from a thermal imaging approach.

Physiology & behavior
Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected ...

Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis.

Journal of neurology
BACKGROUND: Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies.

Deep Learning-Enabled Automated Quality Control for Liver MR Elastography: Initial Results.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.

Multicenter validation of an artificial intelligence (AI)-based platform for the diagnosis of acute appendicitis.

Surgery
BACKGROUND: The current scores used to help diagnose acute appendicitis have a "gray" zone in which the diagnosis is usually inconclusive. Furthermore, the universal use of CT scanning is limited because of the radiation hazards and/or limited resour...

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

Journal of neuroengineering and rehabilitation
BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking pro...

Public perceptions of artificial intelligence in healthcare: ethical concerns and opportunities for patient-centered care.

BMC medical ethics
BACKGROUND: In an effort to improve the quality of medical care, the philosophy of patient-centered care has become integrated into almost every aspect of the medical community. Despite its widespread acceptance, among patients and practitioners, the...

Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model.

BMC pregnancy and childbirth
BACKGROUND: Differential exposure to chronic stressors by race/ethnicity may help explain Black-White inequalities in rates of preterm birth. However, researchers have not investigated the cumulative, interactive, and population-specific nature of ch...

Smartphone application for artificial intelligence-based evaluation of stool state during bowel preparation before colonoscopy.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: Colonoscopy (CS) is an important screening method for the early detection and removal of precancerous lesions. The stool state during bowel preparation (BP) should be properly evaluated to perform CS with sufficient quality. This study ai...