AIMC Topic: Comorbidity

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Tensor Factorization for Precision Medicine in Heart Failure with Preserved Ejection Fraction.

Journal of cardiovascular translational research
Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous clinical syndrome that may benefit from improved subtyping in order to better characterize its pathophysiology and to develop novel targeted therapies. The United States Precis...

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

PloS one
BACKGROUND: The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate predic...

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

PloS one
BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research w...

Plasma Transfusion in Patients With Cirrhosis in China: A Retrospective Multicenter Cohort Study.

Transfusion medicine reviews
Patients with cirrhosis used to be associated with frequent use of blood components because of their complex disorder of hemostasis and bleeding complications. Recent findings have indicated that patients with cirrhosis have a state of "rebalanced" o...

Predictors of in-hospital mortality following major lower extremity amputations in type 2 diabetic patients using artificial neural networks.

BMC medical research methodology
BACKGROUND: Outcome prediction is important in the clinical decision-making process. Artificial neural networks (ANN) have been used to predict the risk of post-operative events, including survival, and are increasingly being used in complex medical ...

Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.

Applied clinical informatics
OBJECTIVE: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5.99 years) using structured and unstructured data from the electronic health record (EHR).

Extracting Information from Electronic Medical Records to Identify the Obesity Status of a Patient Based on Comorbidities and Bodyweight Measures.

Journal of medical systems
Obesity is a chronic disease with an increasing impact on the world's population. In this work, we present a method of identifying obesity automatically using text mining techniques and information related to body weight measures and obesity comorbid...

Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach.

Journal of affective disorders
OBJECTIVE: A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to...

Intestinal helminth infections amongst HIV-infected adults in Mthatha General Hospital, South Africa.

African journal of primary health care & family medicine
BACKGROUND: In South Africa, studies on the prevalence of intestinal helminth co-infection amongst HIV-infected patients as well as possible interactions between these two infection sare limited.