Modeling Topics in DFA-Based Lemmatized Gujarati Text.

Topic modeling is a machine learning algorithm based on statistics that follows unsupervised machine learning techniques for mapping a high-dimensional corpus to a low-dimensional topical subspace, but it could be better. A topic model's topic is expected to be interpretable as a concept, i.e.

Active Cancer Patients Presenting to the Emergency Department with Acute Venous Thromboembolism: A Retrospective Cohort Study on Risks and Outcomes.

Background: There is no prior study that has documented emergency department (ED) outcomes or stratified mortality risks of cancer patients presenting with an acute venous thromboembolism (VTE).

Objective: To evaluate ED treatment of these patients, to document their outcomes, and to identify risk factors associated with death.

Methods: A retrospective cohort study was performed on active cancer patients presenting with deep venous thrombosis or pulmonary embolism to two academic EDs between July 2012 and June 2016.