AIMC Topic: Adult

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Development and validation of a predictive machine learning model for postoperative long-term diabetes insipidus following transsphenoidal surgery for sellar lesions.

Clinical neurology and neurosurgery
OBJECTIVE: Diabetes Insipidus (DI) is a common complication that occurs following transsphenoidal surgery for sellar lesions. DI is usually transient but can be permanent in select patients. Prior studies have described preoperative risk factors for ...

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.

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...

Predicting pregnancy-related pelvic girdle pain using machine learning.

Musculoskeletal science & practice
BACKGROUND: Pregnancy-related pelvic girdle pain (PPGP) is a common complication during gestation which negatively influences pregnant women's quality of life. There are numerous risk factors associated with PPGP, however, there is limited informatio...

Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach.

Computers in biology and medicine
In this work, we developed deep neural networks for the fast and comprehensive estimation of the most salient features of aortic blood flow. These features include velocity magnitude and direction, 3D pressure, and wall shear stress. Starting from 40...

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...

Reflective writing assignments in the era of GenAI: student behavior and attitudes suggest utility, not futility.

Advances in physiology education
Reflective writing is widely used in health sciences education, but overreliance on generative artificial intelligence (GenAI) could undermine the reflective writing process. To explore this concern, students in three undergraduate courses with refle...

A systematic review and sequential explanatory synthesis: Artificial intelligence in healthcare education, a case of nursing.

International nursing review
AIM: This review aims to explore the impact of artificial intelligence (AI) on knowledge acquisition, skills development, and attitudes among nursing students.