AIMC Topic: Retrospective Studies

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Training and validation of a deep learning architecture for the automatic analysis of coronary angiography.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
BACKGROUND: In recent years, the use of deep learning has become more commonplace in the biomedical field and its development will greatly assist clinical and imaging data interpretation. Most existing machine learning methods for coronary angiograph...

Predictors of bleeding event among elderly patients with mechanical valve replacement using random forest model: A retrospective study.

Medicine
Available classification tools and risk factors predicting bleeding events in elderly patients after mechanical valve replacement may not be suitable in Asian populations. Thus, we aimed to identify an accurate model for predicting bleeding in elderl...

A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal Carcinoma.

Journal of the National Cancer Institute
BACKGROUND: Images from magnetic resonance imaging (MRI) are crucial unstructured data for prognostic evaluation in nasopharyngeal carcinoma (NPC). We developed and validated a prognostic system based on the MRI features and clinical data of locoregi...

Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.

Annals of clinical and laboratory science
OBJECTIVE: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. Bacteremia with procalcitonin levels lower than 2.0 ng/mL has not received much attention, and relevant prediction models are lacking. Herein, a panel...

Automated Identification of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning.

JCO clinical cancer informatics
PURPOSE: Although immune checkpoint inhibitors (ICIs) have substantially improved survival in patients with advanced malignancies, they are associated with a unique spectrum of side effects termed immune-related adverse events (irAEs). To ensure trea...

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NLP) can abstract treatment discontinuation rationale from unstructured EMR notes to estimate toxicity...

Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

BMJ health & care informatics
New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in wor...

Segmentation of the Prostate Transition Zone and Peripheral Zone on MR Images with Deep Learning.

Radiology. Imaging cancer
Purpose To develop a deep learning model to delineate the transition zone (TZ) and peripheral zone (PZ) of the prostate on MR images. Materials and Methods This retrospective study was composed of patients who underwent a multiparametric prostate MRI...