AIMC Topic: Comorbidity

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Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning.

Scientific reports
This study aimed to identify the potential pathogenic genes associated with the comorbidity of rheumatoid arthritis (RA) and renal fibrosis (RF). Transcriptomic data related to RA and RF were retrieved from the GEO database. Differential expression g...

Cold receptor TRPM8 as a target for migraine-associated pain and affective comorbidities.

The journal of headache and pain
BACKGROUND: Genetic variations in the Trpm8 gene that encodes the cold receptor TRPM8 have been linked to protection against polygenic migraine, a disabling condition primarily affecting women. Noteworthy, TRPM8 has been recently found in brain areas...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Scientific reports
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative, or missingness) in binary categorical variables in electronic medical records (EMRs) using propens...

The Role of Computed Tomography and Artificial Intelligence in Evaluating the Comorbidities of Chronic Obstructive Pulmonary Disease: A One-Stop CT Scanning for Lung Cancer Screening.

International journal of chronic obstructive pulmonary disease
Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Comorbidities in patients with COPD significantly increase morbidity, mortality, and healthcare costs, posing a significant burden on the management o...

AI-driven analyzes of open-ended responses to assess outcomes of internet-based cognitive behavioral therapy (ICBT) in adolescents with anxiety and depression comorbidity.

Journal of affective disorders
OBJECTIVE: Although patients prefer describing their problems using words, mental health interventions are commonly evaluated using rating scales. Fortunately, recent advances in natural language processing (i.e., AI-methods) yield new opportunities ...

Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).

BMC psychiatry
BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) shows significant challenges as traditional diagnostic methods fail to meet expectations due to patient hesitance and non-psychiatric h...

Machine learning-based prediction of mortality risk in AIDS patients with comorbid common AIDS-related diseases or symptoms.

Frontiers in public health
OBJECTIVE: Early assessment and intervention of Acquired Immune Deficiency Syndrome (AIDS) patients at high risk of mortality is critical. This study aims to develop an optimally performing mortality risk prediction model for AIDS patients with comor...

Robot-Assisted Gait Training in Older Patients with Comorbid Conditions: A Pilot Study.

Experimental aging research
PURPOSE: This study aimed to evaluate the efficacy of robot-assisted gait training (RAGT) in older patients with neurological gait disorder accompanied by various comorbidities.

Explainable machine learning model for assessing health status in patients with comorbid coronary heart disease and depression: Development and validation study.

International journal of medical informatics
BACKGROUND: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and vali...