AIMC Topic: Predictive Value of Tests

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Artificial Intelligence-based Segmentation of Residual Pancreatic Cancer in Resection Specimens Following Neoadjuvant Treatment (ISGPP-2): International Improvement and Validation Study.

The American journal of surgical pathology
Neoadjuvant therapy (NAT) has become routine in patients with borderline resectable pancreatic cancer. Pathologists examine pancreatic cancer resection specimens to evaluate the effect of NAT. However, an automated scoring system to objectively quant...

Machine learning-based Cerebral Venous Thrombosis diagnosis with clinical data.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Cerebral Venous Thrombosis (CVT) poses diagnostic challenges due to the variability in disease course and symptoms. The prognosis of CVT relies on early diagnosis. Our study focuses on developing a machine learning-based screening algorit...

A machine learning tool for identifying patients with newly diagnosed diabetes in primary care.

Primary care diabetes
BACKGROUND AND AIM: It is crucial to identify a diabetes diagnosis early. Create a predictive model utilizing machine learning (ML) to identify new cases of diabetes in primary health care (PHC).

Predicting lower limb lymphedema after cervical cancer surgery using artificial neural network and decision tree models.

European journal of oncology nursing : the official journal of European Oncology Nursing Society
PURPOSE: This study aimed to develop and validate accessible artificial neural network and decision tree models to predict the risk of lower limb lymphedema after cervical cancer surgery.

The premise, promise, and perils of artificial intelligence in critical care cardiology.

Progress in cardiovascular diseases
Artificial intelligence (AI) is an emerging technology with numerous healthcare applications. AI could prove particularly useful in the cardiac intensive care unit (CICU) where its capacity to analyze large datasets in real-time would assist clinicia...

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Progress in cardiovascular diseases
Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-o...

Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translation.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently a...

Multicenter validation of an artificial intelligence (AI)-based platform for the diagnosis of acute appendicitis.

Surgery
BACKGROUND: The current scores used to help diagnose acute appendicitis have a "gray" zone in which the diagnosis is usually inconclusive. Furthermore, the universal use of CT scanning is limited because of the radiation hazards and/or limited resour...