AI Medical Compendium Topic

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Diagnostic Tests, Routine

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Machine learning for the prediction of diabetes-related amputation: a systematic review and meta-analysis of diagnostic test accuracy.

Clinical and experimental medicine
Although machine learning is frequently used in medicine for predictive purposes, its accuracy in diabetes-related amputation (DRA) remains unclear. From establishing the database until December 2024, we conducted a comprehensive search of PubMed, We...

Diagnostic Test Accuracy of artificial intelligence-assisted detection of acute coronary syndrome: A systematic review and meta-analysis.

Computers in biology and medicine
BACKGROUND: Artificial intelligence (AI) has potential uses in healthcare including the detection of health conditions and prediction of health outcomes. Past systematic reviews had reviewed the accuracy of artificial neural networks (ANN) on Electro...

Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study.

Biomedical engineering online
BACKGROUND: This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans.

The Use of Uroflowmetry as a Diagnostic Test.

Current urology reports
PURPOSE OF REVIEW: Uroflowmetry is widely used for initial non-invasive evaluation of lower urinary tract disorders. Current clinical use is mostly restricted to a scrutiny of the maximum flow rate and uroflow pattern recorded by a conventional flowm...

A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.

Scientific data
Urinary tract infection (UTI) is a common disorder. Its diagnosis can be made by microscopic examination of voided urine for markers of infection. This manual technique is technically difficult, time-consuming and prone to inter-observer errors. The ...

Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.

Clinical oral investigations
OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aime...

Implementation of Digital Pathology and Artificial Intelligence in Routine Pathology Practice.

Laboratory investigation; a journal of technical methods and pathology
The advent of affordable technology has significantly influenced the practice of digital pathology, leading to its growing adoption within the pathology community. This review article aimed to outline the latest developments in digital pathology, the...

Validation of Vetscan Imagyst, a diagnostic test utilizing an artificial intelligence deep learning algorithm, for detecting strongyles and Parascaris spp. in equine fecal samples.

Parasites & vectors
BACKGROUND: Current methods for obtaining fecal egg counts in horses are often inaccurate and variable depending on the analyst's skill and experience. Automated digital scanning of fecal sample slides integrated with analysis by an artificial intell...

A meta-analysis of the diagnostic test accuracy of artificial intelligence predicting emergency department dispositions.

BMC medical informatics and decision making
BACKGROUND: The rapid advancement of Artificial Intelligence (AI) has led to its widespread application across various domains, showing encouraging outcomes. Many studies have utilized AI to forecast emergency department (ED) disposition, aiming to f...