AIMC Topic: Comorbidity
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Prospective prediction of anxiety onset in the Canadian longitudinal study on aging (CLSA): A machine learning study.
Journal of affective disorders
Apr 24, 2024
BACKGROUND: Anxiety disorders are among the most common mental health disorders in the middle aged and older population. Because older individuals are more likely to have multiple comorbidities or increased frailty, the impact of anxiety disorders on...
Personality traits as predictors of depression across the lifespan.
Journal of affective disorders
Mar 26, 2024
BACKGROUND: Depression is a major public health concern. A barrier for research has been the heterogeneous nature of depression, complicated by the categorical diagnosis of depression which is based on a cluster of symptoms, each with its own etiolog...
Predicting hypertension control using machine learning.
PloS one
Mar 20, 2024
Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected individuals to severe adverse effects. Though the importance of controlling hypertension is clear, the multitude of therapeutic regimens and patient factors...
Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.
BMC medical informatics and decision making
Feb 14, 2024
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...
The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.
AIDS and behavior
Feb 7, 2024
We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled National COVID Cohort Collaborative (N3C) data released from January 1, 2020 to October 10, 2022. We d...
Prediction of adverse events risk in patients with comorbid post-traumatic stress disorder and alcohol use disorder using electronic medical records by deep learning models.
Drug and alcohol dependence
Jan 9, 2024
BACKGROUND: Identifying co-occurring mental disorders and elevated risk is vital for optimization of healthcare processes. In this study, we will use DeepBiomarker2, an updated version of our deep learning model to predict the adverse events among pa...
Chronic kidney disease and Charlson comorbidity index predict complications after robot-assisted radical cystectomy: A single-center study in Japan.
International journal of urology : official journal of the Japanese Urological Association
Nov 11, 2023
OBJECTIVES: To investigate preoperative patient factors that may predict the occurrence of perioperative complications following robot-assisted radical cystectomy at a single center in Japan.
Deep learning for obstructive sleep apnea diagnosis based on single channel oximetry.
Nature communications
Aug 12, 2023
Obstructive sleep apnea (OSA) is a serious medical condition with a high prevalence, although diagnosis remains a challenge. Existing home sleep tests may provide acceptable diagnosis performance but have shown several limitations. In this retrospect...
Molecular bases of comorbidities: present and future perspectives.
Trends in genetics : TIG
Jul 22, 2023
Co-occurrence of diseases decreases patient quality of life, complicates treatment choices, and increases mortality. Analyses of electronic health records present a complex scenario of comorbidity relationships that vary by age, sex, and cohort under...
Explainable artificial intelligence on life satisfaction, diabetes mellitus and its comorbid condition.
Scientific reports
Jul 19, 2023
This study uses artificial intelligence for testing (1) whether the comorbidity of diabetes and its comorbid condition is very strong in the middle-aged or old (hypothesis 1) and (2) whether major determinants of the comorbidity are similar for diffe...
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