AIMC Topic: Comorbidity

Clear Filters Showing 101 to 110 of 245 articles

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

Nutrients
The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in many countries. This poses a serious threat to the current and near-future health systems, given the association of these conditions with different co...

COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda.

Respiratory medicine
Chronic Obstructive Pulmonary Disease (COPD) is a highly heterogeneous condition projected to become the third leading cause of death worldwide by 2030. To better characterize this condition, clinicians have classified patients sharing certain sympto...

Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

PloS one
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In thi...

Predicting hospital readmission in patients with mental or substance use disorders: A machine learning approach.

International journal of medical informatics
OBJECTIVE: Mental or substance use disorders (M/SUD) are major contributors of disease burden with high risk for hospital readmissions. We sought to develop and evaluate a readmission model using a machine learning (ML) approach.

Unveiling new disease, pathway, and gene associations via multi-scale neural network.

PloS one
Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these prof...

Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs.

Towards Reliable ARDS Clinical Decision Support: ARDS Patient Analytics with Free-text and Structured EMR Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In this work, we utilize a combination of free-text and structured data to build Acute Respiratory Distress Syndrome(ARDS) prediction models and ARDS phenotype clusters. We derived 'Patient Context Vectors' representing patientspecific contextual ARD...