AI Medical Compendium Topic:
Reproducibility of Results

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Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews.

International journal of medical informatics
BACKGROUND: PRISMA-based literature reviews require meticulous scrutiny of extensive textual data by multiple reviewers, which is associated with considerable human effort.

Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
INTRODUCTION: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Despite its reliabilit...

Automatic quantification of scapular and glenoid morphology from CT scans using deep learning.

European journal of radiology
OBJECTIVES: To develop and validate an open-source deep learning model for automatically quantifying scapular and glenoid morphology using CT images of normal subjects and patients with glenohumeral osteoarthritis.

Artificial neural networks for ECG interpretation in acute coronary syndrome: A scoping review.

The American journal of emergency medicine
INTRODUCTION: The electrocardiogram (ECG) is a crucial diagnostic tool in the Emergency Department (ED) for assessing patients with Acute Coronary Syndrome (ACS). Despite its widespread use, the ECG has limitations, including low sensitivity of the S...

Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline.

Scientific reports
As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purificat...

Group-informed attentive framework for enhanced diabetes mellitus progression prediction.

Frontiers in endocrinology
The increasing prevalence of Diabetes Mellitus (DM) as a global health concern highlights the paramount importance of accurately predicting its progression. This necessity has propelled the use of deep learning's advanced analytical and predictive ca...

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Progress in cardiovascular diseases
Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-o...

Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translation.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently a...

Deep Learning-Enabled Automated Quality Control for Liver MR Elastography: Initial Results.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.

Inter-Rater and Intra-Rater Agreement in Scoring Severity of Rodent Cardiomyopathy and Relation to Artificial Intelligence-Based Scoring.

Toxicologic pathology
We previously developed a computer-assisted image analysis algorithm to detect and quantify the microscopic features of rodent progressive cardiomyopathy (PCM) in rat heart histologic sections and validated the results with a panel of five veterinary...