AIMC Topic: Comorbidity

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Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy.

PloS one
Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imagin...

Predicting hospital-acquired pneumonia among schizophrenic patients: a machine learning approach.

BMC medical informatics and decision making
BACKGROUND: Medications are frequently used for treating schizophrenia, however, anti-psychotic drug use is known to lead to cases of pneumonia. The purpose of our study is to build a model for predicting hospital-acquired pneumonia among schizophren...

Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adults.

PloS one
BACKGROUND: Payers and providers still primarily use ordinary least squares (OLS) to estimate expected economic and clinical outcomes for risk adjustment purposes. Penalized linear regression represents a practical and incremental step forward that p...

Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of Human Immunodeficiency Virus, Alcoholism, and Their Comorbidity of Individuals.

Biological psychiatry. Cognitive neuroscience and neuroimaging
The incidence of alcohol use disorder (AUD) in human immunodeficiency virus (HIV) infection is twice that of the rest of the population. This study documents complex radiologically identified, neuroanatomical effects of AUD+HIV comorbidity by identif...

Neurodevelopmental heterogeneity and computational approaches for understanding autism.

Translational psychiatry
In recent years, the emerging field of computational psychiatry has impelled the use of machine learning models as a means to further understand the pathogenesis of multiple clinical disorders. In this paper, we discuss how autism spectrum disorder (...

Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.

BMC medical informatics and decision making
BACKGROUND: Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support...

A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery.

Journal of medical systems
Robot-assisted surgery (RAS) requires a large capital investment by healthcare organizations. The cost of a robotic unit is fixed, so institutions must maximize use of each unit by utilizing all available operating room block time. One way to increas...

Development and Validation of a Machine Learning Algorithm After Primary Total Hip Arthroplasty: Applications to Length of Stay and Payment Models.

The Journal of arthroplasty
BACKGROUND: Value-based payment programs in orthopedics, specifically primary total hip arthroplasty (THA), present opportunities to apply forecasting machine learning techniques to adjust payment models to a specific patient or population. The objec...

Survival outcome prediction in cervical cancer: Cox models vs deep-learning model.

American journal of obstetrics and gynecology
BACKGROUND: Historically, the Cox proportional hazard regression model has been the mainstay for survival analyses in oncologic research. The Cox proportional hazard regression model generally is used based on an assumption of linear association. How...