AIMC Topic: Predictive Value of Tests

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Improved detection of small pulmonary embolism on unenhanced computed tomography using an artificial intelligence-based algorithm - a single centre retrospective study.

The international journal of cardiovascular imaging
To preliminarily verify the feasibility of a deep-learning (DL) artificial intelligence (AI) model to localize pulmonary embolism (PE) on unenhanced chest-CT by comparison with pulmonary artery (PA) CT angiography (CTA). In a monocentric study, we re...

Deep learning model for intravascular ultrasound image segmentation with temporal consistency.

The international journal of cardiovascular imaging
This study was conducted to develop and validate a deep learning model for delineating intravascular ultrasound (IVUS) images of coronary arteries.Using a total of 1240 40-MHz IVUS pullbacks with 191,407 frames, the model for lumen and external elast...

Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.

Journal of the American Heart Association
BACKGROUND: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke o...

Artificial neural network prediction of postoperative complications in papillary thyroid microcarcinoma based on preoperative ultrasonographic features.

Journal of clinical ultrasound : JCU
OBJECTIVE: To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) patients using a deep learning model based on preoperative ultrasonographic features. This study addresses the global rise in PTMC incidence and the cha...

Development of an artificial intelligence-based model to predict early recurrence of neuroendocrine liver metastasis after resection.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
PURPOSE: We sought to develop an artificial intelligence (AI)-based model to predict early recurrence (ER) after curative-intent resection of neuroendocrine liver metastases (NELMs).

Factors for increasing positive predictive value of pneumothorax detection on chest radiographs using artificial intelligence.

Scientific reports
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from...

Thy-DAMP: deep artificial neural network model for prediction of thyroid cancer mortality.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Despite the rising incidence of differentiated thyroid cancer (DTC), mortality rates have remained relatively low yet crucial for effective patient management. This study aims to develop a deep neural network capable of predicting mortality ...

Role of Artificial Intelligence and Machine Learning to Create Predictors, Enhance Molecular Understanding, and Implement Purposeful Programs for Myocardial Recovery.

Methodist DeBakey cardiovascular journal
Heart failure (HF) affects millions of individuals and causes hundreds of thousands of deaths each year in the United States. Despite the public health burden, medical and device therapies for HF significantly improve clinical outcomes and, in a subs...

Development and internal validation of an artificial intelligence-assisted bowel sounds auscultation system to predict early enteral nutrition-associated diarrhoea in acute pancreatitis: a prospective observational study.

British journal of hospital medicine (London, England : 2005)
An artificial intelligence-assisted prediction model for enteral nutrition-associated diarrhoea (ENAD) in acute pancreatitis (AP) was developed utilising data obtained from bowel sounds auscultation. This model underwent validation through a single-...