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Comparing Patient Perception and Physician's Records: Generative AI Performance Evaluation.

Studies in health technology and informatics
Patient perception involves a patient's thoughts and beliefs regarding their health status. It is also associated with medical compliance and outcomes. However, discrepancies often arise between patient perception and physicians' documentation within...

Comparative Analysis of Artificial Intelligence Algorithms for Breast Cancer Detection from Pathological Image in Burkina Faso.

Studies in health technology and informatics
Artificial Intelligence (AI) has revolutionized many fields, including medical imaging. This revolution has enabled the digitization of medical images, the development of algorithms allowing the use of data captured in natural language, and deep lear...

Artificial Intelligence System for Automated Breast Cancer Detection in Pathology in Burkina Faso: Methodology Overview.

Studies in health technology and informatics
The introduction of artificial intelligence (AI) in breast cancer diagnosis in Burkina Faso represents a significant advancement in the field of healthcare. Faced with the public health issue posed by breast cancer, this study focuses on the use of A...

Initial Investigations into Physician Acceptance of Medical AI: Examining Trust, Resistance, Perceived Job Insecurity, and Usage Intentions.

Studies in health technology and informatics
This study evaluated physicians' attitudes towards medical AI across three Taiwanese hospitals, focusing on constructs of trust, resistance, job insecurity, and adoption willingness, with a survey based on the Dual-factor Model yielding 282 responses...

Machine Learning with Clinical and Intraoperative Biosignal Data for Predicting Cardiac Surgery-Associated Acute Kidney Injury.

Studies in health technology and informatics
Early identification of patients at high risk of cardiac surgery-associated acute kidney injury (CSA-AKI) is crucial for its prevention. We aimed to leverage perioperative clinical and intraoperative biosignal data to develop machine learning models ...

Deep Learning Based Automatic Fibroglandular Tissue Segmentation in Breast Magnetic Resonance Imaging Screening.

Studies in health technology and informatics
In light of the global increase in breast cancer cases and the crucial importance of the density of fibroglandular tissue (FGT) in assessing risk and predicting the course of the disease, the accurate measurement of FGT emerges as a significant chall...

Prediction of Poor Glycemic Control in Children with Type 1 Diabetes.

Studies in health technology and informatics
This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.

Harnessing the Power of Machine Learning and Electronic Health Records to Support Child Abuse and Neglect Identification in Emergency Department Settings.

Studies in health technology and informatics
Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often complex. Our study developed a machine learning model using structured and unstructured electronic health record (EHR) data to predict when children ...

From Data Mining of Public Sources to Clinical Decision Support in Personalized Medicine.

Studies in health technology and informatics
Personalized medicine enables precise tumor treatment for a patient's molecular genetic profile. To devise optimal targeted treatment plans for patients in a molecular tumor board, physicians must consider alterations on gene- and proteins levels but...