AIMC Topic: Predictive Value of Tests

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A Machine Learning-derived Risk Score Improves Prediction of Outcomes After LVAD Implantation: An Analysis of the INTERMACS Database.

Journal of cardiac failure
BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implantation emphasize the importance of accurately assessing patients' risk before surgery. This study assesses the Machine Learning Assessment of Risk and E...

Predictive performance of machine learning models for kidney complications following coronary interventions: a systematic review and meta-analysis.

International urology and nephrology
BACKGROUND: Acute kidney injury (AKI) and contrast-induced nephropathy (CIN) are common complications following percutaneous coronary intervention (PCI) or coronary angiography (CAG), presenting significant clinical challenges. Machine learning (ML) ...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BMC gastroenterology
BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further improved accuracy. In this study, we aimed to construct a combined prognostic model using deep learning-...

Beyond MELD Score: Association of Machine Learning-derived CT Body Composition with 90-Day Mortality Post Transjugular Intrahepatic Portosystemic Shunt Placement.

Cardiovascular and interventional radiology
PURPOSE: To determine the association of machine learning-derived CT body composition and 90-day mortality after transjugular intrahepatic portosystemic shunt (TIPS) and to assess its predictive performance as a complement to Model for End-Stage Live...

Early prediction of radiotherapy outcomes in pharyngeal cancer using deep learning on baseline [18F]Fluorodeoxyglucose positron emission Tomography/Computed tomography.

European journal of radiology
OBJECTIVES: This study aimed to develop an integrated segmentation-free deep learning (DL) framework to predict multiple aspects of radiotherapy outcome in pharyngeal cancer patients by analyzing pretreatment 18F-fluorodeoxyglucose (18F-FDG) positron...

Machine learning approaches toward an understanding of acute kidney injury: current trends and future directions.

The Korean journal of internal medicine
Acute kidney injury (AKI) is a significant health challenge associated with adverse patient outcomes and substantial economic burdens. Many authors have sought to prevent and predict AKI. Here, we comprehensively review recent advances in the use of ...

Predicting Portal Pressure Gradient in Patients with Decompensated Cirrhosis: A Non-invasive Deep Learning Model.

Digestive diseases and sciences
BACKGROUND: A high portal pressure gradient (PPG) is associated with an increased risk of failure to control esophagogastric variceal hemorrhage and refractory ascites in patients with decompensated cirrhosis. However, direct measurement of PPG is in...

Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.

Abdominal radiology (New York)
PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular carcinoma (HCC) for the prediction of response to Yttrium 90 radiation segmentectomy.