AIMC Topic: Humans

Clear Filters Showing 21171 to 21180 of 95995 articles

A deep learning approach for cervical cord injury severity determination through axial and sagittal magnetic resonance imaging segmentation and classification.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
STUDY DESIGN: Cross-sectional Database Study.

Economical hybrid novelty detection leveraging global aleatoric semantic uncertainty for enhanced MRI-based ACL tear diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study presents an innovative hybrid deep learning (DL) framework that reformulates the sagittal MRI-based anterior cruciate ligament (ACL) tear classification task as a novelty detection problem to tackle class imbalance. We introduce a highly d...

Diagnostic accuracy of a machine learning algorithm using point-of-care high-sensitivity cardiac troponin I for rapid rule-out of myocardial infarction: a retrospective study.

The Lancet. Digital health
BACKGROUND: Point-of-care (POC) high-sensitivity cardiac troponin (hs-cTn) assays have been shown to provide similar analytical precision despite substantially shorter turnaround times compared with laboratory-based hs-cTn assays. We applied the prev...

Mitigating the risk of artificial intelligence bias in cardiovascular care.

The Lancet. Digital health
Digital health technologies can generate data that can be used to train artificial intelligence (AI) algorithms, which have been particularly transformative in cardiovascular health-care delivery. However, digital and health-care data repositories th...

The potential for large language models to transform cardiovascular medicine.

The Lancet. Digital health
Cardiovascular diseases persist as the leading cause of death globally and their early detection and prediction remain a major challenge. Artificial intelligence (AI) tools can help meet this challenge as they have considerable potential for early di...

Challenges for augmenting intelligence in cardiac imaging.

The Lancet. Digital health
Artificial Intelligence (AI), through deep learning, has brought automation and predictive capabilities to cardiac imaging. However, despite considerable investment, tangible health-care cost reductions remain unproven. Although AI holds promise, the...

Artificial neural network inference analysis identified novel genes and gene interactions associated with skeletal muscle aging.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study ...

Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features.

Rheumatology international
The use of artificial intelligence (AI) in high-resolution computed tomography (HRCT) for diagnosing systemic sclerosis-associated interstitial lung disease (SSc-ILD) is relatively limited. This study aimed to analyse lung HRCT images of patients wit...

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

Thoracic cancer
BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical tre...