AIMC Topic: Predictive Value of Tests

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Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients.

BMC geriatrics
BACKGROUND: Depression is a common complication after a stroke that may lead to increased disability and decreased quality of life. The objective of this study was to develop and validate an interpretable predictive model to assess the risk of depres...

Optimizing heart disease diagnosis with advanced machine learning models: a comparison of predictive performance.

BMC cardiovascular disorders
Cardiovascular disease is the leading cause of mortality globally, necessitating precise and prompt predictive instruments to enhance patient outcomes. In recent years, machine learning methodologies have demonstrated significant potential in enhanci...

Ovarian masses suggested for MRI examination: assessment of deep learning models based on non-contrast-enhanced MRI sequences for predicting malignancy.

Abdominal radiology (New York)
PURPOSE: We aims to assessed and compare four deep learning(DL) models using non-contrast-enhanced magnetic resonance imaging(MRI) to differentiate benign from malignant ovarian tumors, considering diagnostic efficacy and associated development costs...

Predicting postoperative nausea and vomiting using machine learning: a model development and validation study.

BMC anesthesiology
BACKGROUND: Postoperative nausea and vomiting (PONV) is a frequently observed complication in patients undergoing surgery under general anesthesia. Moreover, it is a frequent cause of distress and dissatisfaction in the early postoperative period. Cu...

Predicting complications after laparoscopic surgery for ureteropelvic junction obstruction using machine learning models: a retrospective cohort study.

World journal of urology
PURPOSES: Postoperative complications in patients with ureteropelvic junction obstruction (UPJO) negatively impact surgical outcomes and may necessitate redo surgery. We aimed to predict the occurrence of postoperative complications in these patients...