AIMC Topic: Longitudinal Studies

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Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China.

Frontiers in public health
BACKGROUND: Considering that the previously developed mortality prediction models have limited applications to the Chinese population, a questionnaire-based prediction model is of great importance for its accuracy and convenience in clinical practice...

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks.

Scientific reports
Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, preoperative risk-reduction, and postoperative resource use. We hypothesized that multi-task deep learning models would outperform conventional machin...

A More Posterior Tibial Tubercle (Decreased Sagittal Tibial Tubercle-Trochlear Groove Distance) Is Significantly Associated With Patellofemoral Joint Degenerative Cartilage Change: A Deep Learning Analysis.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To perform patellofemoral joint (PFJ) geometric measurements on knee magnetic resonance imaging scans and determine their relations with chondral lesions in a multicenter cohort using deep learning.

EMG-driven shared human-robot compliant control for in-hand object manipulation in hand prostheses.

Journal of neural engineering
. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulating...

VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer's disease prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Mild cognitive impairment (MCI) is a transitional state between normal aging and Alzheimer's disease (AD), and accurately predicting the progression trend of MCI is critical to the early prevention and treatment of AD. Brain...

Overtriage, Undertriage, and Value of Care after Major Surgery: An Automated, Explainable Deep Learning-Enabled Classification System.

Journal of the American College of Surgeons
BACKGROUND: In single-institution studies, overtriaging low-risk postoperative patients to ICUs has been associated with a low value of care; undertriaging high-risk postoperative patients to general wards has been associated with increased mortality...

Urologic latency time during uroflow stop test with electromyography: an incontinence detector in rehabilitation after robotic radical prostatectomy.

European journal of physical and rehabilitation medicine
BACKGROUND: Stress urinary incontinence (UI) is the most common presentation following robot-assisted radical prostatectomy (RARP), but a postoperative non-invasive and objective test is still lacking. To assess pelvic floor integrity after RARP, we ...

A validated artificial intelligence-based pipeline for population-wide primary immunodeficiency screening.

The Journal of allergy and clinical immunology
BACKGROUND: Identification of patients with underlying inborn errors of immunity and inherent susceptibility to infection remains challenging. The ensuing protracted diagnostic odyssey for such patients often results in greater morbidity and suboptim...

Smart home technology to support older people's quality of life: A longitudinal pilot study.

International journal of older people nursing
AIM: This pilot study aimed to explore the impact of Smart Home technology to support older people's quality of life, particularly for those who live alone.

Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study.

Cells
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for ...