AIMC Topic: Humans

Clear Filters Showing 15351 to 15360 of 95995 articles

Developing an AI-Based clinical decision support system for basal insulin titration in type 2 diabetes in primary Care: A Mixed-Methods evaluation using heuristic Analysis, user Feedback, and eye tracking.

International journal of medical informatics
BACKGROUND AND AIM: The progressive nature of type 2 diabetes often, in time, necessitates basal insulin therapy to achieve glycemic targets. However, despite standardized titration algorithms, many people remain poorly controlled after initiating in...

Artificial Doctors: Performance of Chatbots as a Tool for Patient Education on Keratoconus.

Eye & contact lens
PURPOSE: We aimed to compare the answers given by ChatGPT, Bard, and Copilot and that obtained from the American Academy of Ophthalmology (AAO) website to patient-written questions related to keratoconus in terms of accuracy, understandability, actio...

Knowledge domain and frontier trends of artificial intelligence applied in solid organ transplantation: A visualization analysis.

International journal of medical informatics
BACKGROUND: Solid organ transplantation (SOT) is vital for end-stage organ failure but faces challenges like organ shortage and rejection. Artificial intelligence (AI) offers potential to improve outcomes through better matching, success prediction, ...

Machine Learning-Based Pathomics Model Predicts Angiopoietin-2 Expression and Prognosis in Hepatocellular Carcinoma.

The American journal of pathology
Angiopoietin-2 (ANGPT2) shows promise as prognostic marker and therapeutic target in hepatocellular carcinoma (HCC). However, assessing ANGPT2 expression and prognostic potential using histopathology images viewed with naked eye is challenging. Herei...

Knee osteoarthritis severity detection using deep inception transfer learning.

Computers in biology and medicine
Osteoarthritis (OA) is a prevalent condition resulting in physical limitations. Early detection of OA is critical to effectively manage this condition. However, the diagnosis of early-stage arthritis remains challenging. The Kellgren and Lawrence (KL...

MEFA-Net: A mask enhanced feature aggregation network for polyp segmentation.

Computers in biology and medicine
Accurate polyp segmentation is crucial for early diagnosis and treatment of colorectal cancer. This is a challenging task for three main reasons: (i) the problem of model overfitting and weak generalization due to the multi-center distribution of dat...

Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

Radiological physics and technology
This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms...

Deep Learning-Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell...

Validation of AI-driven measurements for hip morphology assessment.

European journal of radiology
RATIONALE AND OBJECTIVES: Accurate assessment of hip morphology is crucial for the diagnosis and management of hip pathologies. Traditional manual measurements are prone to mistakes and inter- and intra-reader variability. Artificial intelligence (AI...

Using Machine Learning to Predict Weight Gain in Adults: an Observational Analysis From the All of Us Research Program.

The Journal of surgical research
INTRODUCTION: Obesity, defined as a body mass index ≥30 kg/m, is a major public health concern in the United States. Preventative approaches are essential, but they are limited by an inability to accurately predict individuals at highest risk of weig...