AIMC Topic: Retrospective Studies

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Artificial Intelligence-Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI.

Investigative radiology
OBJECTIVES: We investigated artificial intelligence (AI)-based classification of benign and malignant breast lesions imaged with a multiparametric breast magnetic resonance imaging (MRI) protocol with ultrafast dynamic contrast-enhanced MRI, T2-weigh...

Deep transfer learning-based prostate cancer classification using 3 Tesla multi-parametric MRI.

Abdominal radiology (New York)
PURPOSE: The purpose of the study was to propose a deep transfer learning (DTL)-based model to distinguish indolent from clinically significant prostate cancer (PCa) lesions and to compare the DTL-based model with a deep learning (DL) model without t...

Usefulness of Deep Learning Analysis for the Diagnosis of Malignancy in Intraductal Papillary Mucinous Neoplasms of the Pancreas.

Clinical and translational gastroenterology
OBJECTIVES: Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions of pancreatic adenocarcinoma. Artificial intelligence (AI) is a mathematical concept whose implementation automates learning and recognizing data patterns. The aim of ...

Machine learning-based preoperative predictive analytics for lumbar spinal stenosis.

Neurosurgical focus
OBJECTIVEPatient-reported outcome measures (PROMs) following decompression surgery for lumbar spinal stenosis (LSS) demonstrate considerable heterogeneity. Individualized prediction tools can provide valuable insights for shared decision-making. The ...

Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography.

Korean journal of radiology
OBJECTIVE: To investigate whether a computer-aided diagnosis (CAD) system based on a deep learning framework (deep learning-based CAD) improves the diagnostic performance of radiologists in differentiating between malignant and benign masses on breas...

Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.

JAMA cardiology
IMPORTANCE: For patients with chronic kidney disease (CKD), hyperkalemia is common, associated with fatal arrhythmias, and often asymptomatic, while guideline-directed monitoring of serum potassium is underused. A deep-learning model that enables non...

Machine Learning-Based Model for Prediction of Outcomes in Acute Stroke.

Stroke
Background and Purpose- The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the medical field because of their high accuracy. Thi...

Prediction of ISUP grading of clear cell renal cell carcinoma using support vector machine model based on CT images.

Medicine
BACKGROUND: To explore whether radiomics combined with computed tomography (CT) images can be used to establish a model for differentiating high grade (International Society of Urological Pathology [ISUP] grade III-IV) from low-grade (ISUP I-II) clea...