AIMC Topic: Comorbidity

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Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).

Critical care medicine
OBJECTIVES: Delirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a to...

Use of Telepresence Robots in Glaucoma Patient Education.

Journal of glaucoma
PRCIS: Telepresence robots (TR) present the versatility to effectively provide remote educational sessions for patients affected by glaucoma to improve disease knowledge. Given COVID-19's effect on clinical practice, TR can maintain social distancing...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

JAMA psychiatry
IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to yo...

Drivers of Prolonged Hospitalization Following Spine Surgery: A Game-Theory-Based Approach to Explaining Machine Learning Models.

The Journal of bone and joint surgery. American volume
BACKGROUND: Understanding the interactions between variables that predict prolonged hospital length of stay (LOS) following spine surgery can help uncover drivers of this risk in patients. This study utilized a novel game-theory-based approach to dev...

Temporal changes of quantitative CT findings from 102 patients with COVID-19 in Wuhan, China: A longitudinal study.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Computed tomography (CT) imaging combined with artificial intelligence is important in the diagnosis and prognosis of lung diseases.

Phenotypic clustering of heart failure with preserved ejection fraction reveals different rates of hospitalization.

Journal of cardiovascular medicine (Hagerstown, Md.)
AIMS: Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions.

Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associ...

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence.

Reviews in cardiovascular medicine
Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discover...