BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical al...
BMC medical informatics and decision making
May 8, 2019
OBJECTIVE: Assessing risks of bias in randomized controlled trials (RCTs) is an important but laborious task when conducting systematic reviews. RobotReviewer (RR), an open-source machine learning (ML) system, semi-automates bias assessments. We cond...
Background Mammographic density improves the accuracy of breast cancer risk models. However, the use of breast density is limited by subjective assessment, variation across radiologists, and restricted data. A mammography-based deep learning (DL) mod...
BACKGROUND AND AIMS: Although grayscale intravascular ultrasound (IVUS) is commonly used for assessing coronary lesion morphology and optimizing stent implantation, detection of vulnerable plaques by IVUS remains challenging. We aimed to develop mach...
Risk stratification of patients with gastrointestinal bleeding (GIB) is recommended, but current risk assessment tools have variable performance. Machine learning (ML) has promise to improve risk assessment. We performed a systematic review to evalua...
OBJECTIVE: To develop a predictive mathematical model for the early identification of ankylosing spondylitis (AS) based on the medical and pharmacy claims history of patients with and without AS.
BACKGROUND: Building cancer risk models from real-world data requires overcoming challenges in data preprocessing, efficient representation, and computational performance. We present a case study of a cloud-based approach to learning from de-identifi...
Investigation of the clinical potential of extensive phenotype data and machine learning (ML) in the prediction of mortality in acute coronary syndrome (ACS). The value of ML and extensive clinical data was analyzed in a retrospective registry stud...
There is paucity of literature about the validation of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator for prediction of outcomes after robot-assisted radical cystectomy (RARC). We ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.