AIMC Topic: Adult

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Prediction of endoscopic restenosis after endoscopic balloon dilation in patients with Crohn's disease: a machine learning approach.

Surgical endoscopy
BACKGROUND: Endoscopic balloon dilation (EBD) is recognized as a minimally invasive and effective procedure for managing intestinal stenosis in patients with Crohn's disease (CD). It offers an alternative to surgery and has been shown to improve the ...

Evolution of Cortical Lesions and Function-Specific Cognitive Decline in People With Multiple Sclerosis.

Neurology
BACKGROUND AND OBJECTIVES: Cortical lesions in multiple sclerosis (MS) severely affect cognition, but their longitudinal evolution and impact on specific cognitive functions remain understudied. This study investigates the evolution of function-speci...

The impact of machine learning on physical activity-related health outcomes: A systematic review and meta-analysis.

International nursing review
AIM: To analyze randomized controlled trials evaluating the effectiveness of machine learning (ML)-based interventions in promoting physical activity.

Attention to early stages: predicting acute kidney injury in a post cardiosurgical ICU setting using an inclusive time-to-event model.

Computers in biology and medicine
BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that is known to have multifaceted impacts. However, as AKI is often detected too late, early prediction is crucial for timely intervention.

Can Gpt-4o Accurately Diagnose Trauma X-Rays? A Comparative Study with Expert Evaluations.

The Journal of emergency medicine
BACKGROUND: The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process visual data, presenting a novel opportunity for radiographic evaluation in trauma patients.

MRI-based multimodal AI model enables prediction of recurrence risk and adjuvant therapy in breast cancer.

Pharmacological research
Timely intervention and improved prognosis for breast cancer patients rely on early metastasis risk detection and accurate treatment predictions. This study introduces an advanced multimodal MRI and AI-driven 3D deep learning model, termed the 3D-MMR...

Explainable machine learning for movement disorders - Classification of tremor and myoclonus.

Computers in biology and medicine
BACKGROUND: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools.

Development and Validation of an Explainable Machine Learning Model for Warning of Hepatitis E Virus-Related Acute Liver Failure.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Early identification of patients with acute hepatitis E (AHE) who are at high risk of progressing to hepatitis E virus-related acute liver failure (HEV-ALF) is crucial for enabling timely monitoring and intervention. This multice...

Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is one of the most accurate methods for determining the originating layer of subepithelial lesions (SELs). However, the accuracy is greatly influenced by the expertise and proficiency of the endoscopist. In thi...

An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net.

NMR in biomedicine
Quantitative susceptibility mapping (QSM) provides the spatial distribution of magnetic susceptibility within tissues through sequential steps: phase unwrapping and echo combination, mask generation, background field removal, and dipole inversion. Ac...