Perceptions of preparedness, timing of cancer diagnosis, and objective emergency preparedness among gynecological cancer patients in Puerto Rico before and after Hurricane Maria.

Objectives: This study investigated the impact of cancer diagnosis status, individual feelings of preparedness, and other covariates on objective emergency preparedness among women diagnosed with gynecological cancers before or after the 2017 Hurricanes Irma and Maria in Puerto Rico.

Methods: This study included 240 women who were interviewed by telephone from 9/2019-11/2020. Objective emergency preparedness was assessed using a list of six items.

Machine-Learning-Based In-Hospital Mortality Prediction for Transcatheter Mitral Valve Repair in the United States.

Background: Transcatheter mitral valve repair (TMVR) utilization has increased significantly in the United States over the last years. Yet, a risk-prediction tool for adverse events has not been developed. We aimed to generate a machine-learning-based algorithm to predict in-hospital mortality after TMVR.

Machine Learning Algorithm for Predicting Warfarin Dose in Caribbean Hispanics Using Pharmacogenetic Data.

Despite some previous examples of successful application to the field of pharmacogenomics, the utility of machine learning (ML) techniques for warfarin dose predictions in Caribbean Hispanic patients has yet to be fully evaluated. This study compares seven ML methods to predict warfarin dosing in Caribbean Hispanics. This is a secondary analysis of genetic and non-genetic clinical data from 190 cardiovascular Hispanic patients.

Machine Learning Prediction Models for In-Hospital Mortality After Transcatheter Aortic Valve Replacement.

Objectives: This study sought to develop and compare an array of machine learning methods to predict in-hospital mortality after transcatheter aortic valve replacement (TAVR) in the United States.

Background: Existing risk prediction tools for in-hospital complications in patients undergoing TAVR have been designed using statistical modeling approaches and have certain limitations.

Methods: Patient data were obtained from the National Inpatient Sample database from 2012 to 2015.