AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Follow-Up Studies

Showing 221 to 230 of 723 articles

Clear Filters

In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency Department.

Journal of the American Heart Association
Background Classical ST-T waveform changes on standard 12-lead ECG have limited sensitivity in detecting acute coronary syndrome (ACS) in the emergency department. Numerous novel ECG features have been previously proposed to augment clinicians' decis...

Vascular Aging Detected by Peripheral Endothelial Dysfunction Is Associated With ECG-Derived Physiological Aging.

Journal of the American Heart Association
Background An artificial intelligence algorithm that detects age using the 12-lead ECG has been suggested to signal "physiologic age." This study aimed to investigate the association of peripheral microvascular endothelial function (PMEF) as an index...

Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images.

Scientific reports
As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past decade. On the other hand, recent advances in deep learning and transfer learning have shown significant potential in the quanti...

Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.

American journal of ophthalmology
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm's predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects.

Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation.

Hepatology communications
Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HCC). Steatotic HCC can be reliably detected by magnetic resonance imaging. To determine the clinical relevance of this radiological variant, we include...

Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.

Ophthalmology
PURPOSE: Rule-based approaches to determining glaucoma progression from visual fields (VFs) alone are discordant and have tradeoffs. To detect better when glaucoma progression is occurring, we used a longitudinal data set of merged VF and clinical da...

Artificial neural networks for simultaneously predicting the risk of multiple co-occurring symptoms among patients with cancer.

Cancer medicine
Patients with cancer often exhibit multiple co-occurring symptoms which can impact the type of treatment received, recovery, and long-term health. We aim to simultaneously predict the risk of three symptoms: severe pain, moderate-severe depression, a...

Outcomes of surgical and/or medical treatment in patients with prolactinomas during long-term follow-up: a retrospective single-centre study.

Hormone molecular biology and clinical investigation
OBJECTIVES: Prolactinoma is the most common cause of pituitary tumours. Current medical guidelines recommend dopamine agonists (cabergoline or bromocriptine) as the initial therapy for prolactinoma. However, surgical removal can also be considered in...