AIMC Topic: Middle Aged

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Factors influencing the estimation of phacoemulsification procedure time in cataract surgery: Analysis using neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Realistic and accurate estimation of the surgery duration is one of the key factors influencing the optimization of hospital work and, consequently, the planning and management of the budget. In the present study, the author...

Automated engineered-stone silicosis screening and staging using Deep Learning with X-rays.

Computers in biology and medicine
Silicosis, a debilitating occupational lung disease caused by inhaling crystalline silica, continues to be a significant global health issue, especially with the increasing use of engineered stone (ES) surfaces containing high silica content. Traditi...

Deep learning-driven multi-class classification of brain strokes using computed tomography: A step towards enhanced diagnostic precision.

European journal of radiology
OBJECTIVE: To develop and validate deep learning models leveraging CT imaging for the prediction and classification of brain stroke conditions, with the potential to enhance accuracy and support clinical decision-making.

Keeping AI on Track: Regular monitoring of algorithmic updates in mammography.

European journal of radiology
PURPOSE: To demonstrate a method of benchmarking the performance of two consecutive software releases of the same commercial artificial intelligence (AI) product to trained human readers using the Personal Performance in Mammographic Screening scheme...

AI for fracture diagnosis in clinical practice: Four approaches to systematic AI-implementation and their impact on AI-effectiveness.

European journal of radiology
PURPOSE: Artificial Intelligence (AI) has been shown to enhance fracture-detection-accuracy, but the most effective AI-implementation in clinical practice is less well understood. In the current study, four approaches to AI-implementation are evaluat...

Enhanced non-invasive machine learning approach for early colorectal cancer detection: Predictive modeling and validation in a Jordanian cohort.

Computers in biology and medicine
BACKGROUND: Colorectal cancer (CRC) ranks as the third most prevalent cancer worldwide, posing significant public health challenges. Late-stage detection often results in poor treatment outcomes, elevating mortality rates. The economic and psychologi...

Deep Learning in Knee MRI: A Prospective Study to Enhance Efficiency, Diagnostic Confidence and Sustainability.

Academic radiology
RATIONALE AND OBJECTIVES: The objective of this study was to evaluate a combination of deep learning (DL)-reconstructed parallel acquisition technique (PAT) and simultaneous multislice (SMS) acceleration imaging in comparison to conventional knee ima...

Evaluation of blood- and urine-derived biomarkers for machine learning prediction models of osteoarthritis in elderly patients: A feasibility study.

Computer methods and programs in biomedicine
BACKGROUND: Osteoarthritis (OA) is a common degenerative joint disease, particularly affecting individuals aged >50 years. It deteriorates quality of life and restricts physical activity in the elderly. Early diagnosis of OA is crucial for effective ...

Artificial Intelligence-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms.

JAMA cardiology
IMPORTANCE: Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) may enable large-scale com...