AIMC Topic: Longitudinal Studies

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Annotating risk factors for heart disease in clinical narratives for diabetic patients.

Journal of biomedical informatics
The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on identifying risk factors for heart disease (specifically, Cardiac Artery Disease) in clinical narratives. For this track, we used a "light" annotation paradigm...

Prediction of remission in obsessive compulsive disorder using a novel machine learning strategy.

International journal of methods in psychiatric research
The study objective was to apply machine learning methodologies to identify predictors of remission in a longitudinal sample of 296 adults with a primary diagnosis of obsessive compulsive disorder (OCD). Random Forests is an ensemble machine learning...

Variable importance and prediction methods for longitudinal problems with missing variables.

PloS one
We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patie...

The use of natural language processing of infusion notes to identify outpatient infusions.

Pharmacoepidemiology and drug safety
PURPOSE: Outpatient infusions are commonly missing in Veterans Health Affairs (VHA) pharmacy dispensing data sets. Currently, Healthcare Common Procedure Coding System (HCPCS) codes are used to identify outpatient infusions, but concerns exist if the...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

European child & adolescent psychiatry
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...

Evaluation of artificial-intelligence-based liver segmentation and its application for longitudinal liver volume measurement.

Abdominal radiology (New York)
BACKGROUND: Accurate liver-volume measurements from CT scans are essential for treatment planning, particularly in liver resection cases, to avoid postoperative liver failure. However, manual segmentation is time-consuming and prone to variability. A...

Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method.

European journal of psychotraumatology
Approximately 70% of individuals globally experience at least one traumatic event in their lifetimes, potentially leading to posttraumatic stress disorder (PTSD). Understanding the development of PTSD and devising effective prevention and treatment ...

Association and prediction of serum lipid profiles with incident stroke in the CHARLS cohort: A machine learning analysis.

Medicine
Using the 2011 baseline data of the China health and retirement longitudinal study, we examined the associations between serum lipids and other risk factors and incident stroke, and developed and compared multiple machine learning models for stroke-r...

Clinical Utility of Pulmonary Function Testing in Assessing Longitudinal Outcomes of Deployed Veterans with Preserved Spirometry.

Annals of the American Thoracic Society
Deployment to the Southwest Asia theater of military operations is associated with new-onset respiratory symptoms, yet commonly used parameters on pulmonary function testing (PFT) are typically reported to be within the normal range for most deploye...

Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longitudinal study.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) is characterized by significant heterogeneity in treatment response, with inflammation hypothesized to play a role in its pathophysiology. Peripheral inflammatory biomarkers, such as the neutrophil-to-lymph...