AIMC Topic:
Middle Aged

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Patient Perspectives on Conversational Artificial Intelligence for Atrial Fibrillation Self-Management: Qualitative Analysis.

Journal of medical Internet research
BACKGROUND: Conversational artificial intelligence (AI) allows for engaging interactions, however, its acceptability, barriers, and enablers to support patients with atrial fibrillation (AF) are unknown.

Augmenting rehabilitation robotics with spinal cord neuromodulation: A proof of concept.

Science robotics
Rehabilitation robotics aims to promote activity-dependent reorganization of the nervous system. However, people with paralysis cannot generate sufficient activity during robot-assisted rehabilitation and, consequently, do not benefit from these ther...

The Perceptions of Potential Prerequisites for Artificial Intelligence in Danish General Practice: Vignette-Based Interview Study Among General Practitioners.

JMIR medical informatics
BACKGROUND: Artificial intelligence (AI) has been deemed revolutionary in medicine; however, no AI tools have been implemented or validated in Danish general practice. General practice in Denmark has an excellent digitization system for developing an...

Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.

Aging clinical and experimental research
BACKGROUND: Early prediction of progression in dementia is of major importance for providing patients with adequate clinical care, with considerable impact on the organization of the whole healthcare system.

Querying the capability of the post-HoLEP endoscopic aspect of the membranous urethral mucosa in predicting urinary incontinence: a prospective AI-based analysis.

World journal of urology
INTRODUCTION: Transient stress urinary incontinence (SUI) after holmium laser enucleation of prostate (HoLEP) is commonly linked to intraoperative injury of the external urethral sphincter (EUS). We assessed the reliability of the post-HoLEP endoscop...

Development of a machine learning-based predictive model for maxillary sinus cysts and exploration of clustering patterns.

Head & face medicine
BACKGROUND AND OBJECTIVE: There are still many controversies about the factors influencing maxillary sinus cysts and their clinical management. This study aims to construct a prediction model of maxillary sinus cyst and explore its clustering pattern...

Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.

Scientific reports
Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification ...

Machine learning-based prediction of mortality risk in AIDS patients with comorbid common AIDS-related diseases or symptoms.

Frontiers in public health
OBJECTIVE: Early assessment and intervention of Acquired Immune Deficiency Syndrome (AIDS) patients at high risk of mortality is critical. This study aims to develop an optimally performing mortality risk prediction model for AIDS patients with comor...

Early differential diagnosis models of Talaromycosis and Tuberculosis in HIV-negative hosts using clinical data and machine learning.

Journal of infection and public health
BACKGROUND: Talaromyces marneffei is an emerging pathogen, and the number of infections in HIV-negative individuals is increasing. In HIV-negative individuals, talaromycosis is usually misdiagnosed as another disease, especially tuberculosis (TB).