AIMC Topic: Comorbidity
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Integrating multi-task and cost-sensitive learning for predicting mortality risk of chronic diseases in the elderly using real-world data.
International journal of medical informatics
Jul 25, 2024
BACKGROUND AND OBJECTIVE: Real-world data encompass population diversity, enabling insights into chronic disease mortality risk among the elderly. Deep learning excels on large datasets, offering promise for real-world data. However, current models f...
Predicting Depression, Anxiety, and Their Comorbidity among Patients with Breast Cancer in China Using Machine Learning: A Multisite Cross-Sectional Study.
Depression and anxiety
Jun 21, 2024
Depression and anxiety are highly prevalent among patients with breast cancer. We tested the capacity of personal resources (psychological resilience, social support, and process of recovery) for predicting depression, anxiety, and comorbid depressio...
Development of a machine learning-based risk model for postoperative complications of lung cancer surgery.
Surgery today
Jun 19, 2024
PURPOSE: To develop a comorbidity risk score specifically for lung resection surgeries.
Prediction of pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II based on clinical risk.
PloS one
Jun 4, 2024
OBJECTIVE: To assess the effectiveness of different machine learning models in estimating the pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II diagnosis, based on the clinical risk index determined by the a...
Natural language processing to identify and characterize spondyloarthritis in clinical practice.
RMD open
May 24, 2024
OBJECTIVE: This study aims to use a novel technology based on natural language processing (NLP) to extract clinical information from electronic health records (EHRs) to characterise the clinical profile of patients diagnosed with spondyloarthritis (S...
Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1.
Sleep medicine
May 23, 2024
BACKGROUND: Major depression disorder (MDD) forms a common psychiatric comorbidity among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often overlooked by neurologists. Currently, there is a lack of effective methods f...
Natural language processing augments comorbidity documentation in neurosurgical inpatient admissions.
PloS one
May 9, 2024
OBJECTIVE: To establish whether or not a natural language processing technique could identify two common inpatient neurosurgical comorbidities using only text reports of inpatient head imaging.
Identification of sleep phenotypes in COPD using machine learning-based cluster analysis.
Respiratory medicine
May 6, 2024
BACKGROUND: Disturbed sleep in patients with COPD impact quality of life and predict adverse outcomes.
Deep Survival Analysis With Latent Clustering and Contrastive Learning.
IEEE journal of biomedical and health informatics
May 6, 2024
Survival analysis is employed to analyze the time before the event of interest occurs, which is broadly applied in many fields. The existence of censored data with incomplete supervision information about survival outcomes is one key challenge in sur...
Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.
PloS one
Apr 25, 2024
The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilitate the identification of patients at highest risk of adverse outcomes is a priority. The study objectives are to develop population-scale predictive ...
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