AIMC Topic: Severity of Illness Index

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Robotic telepresence versus standardly supervised stroke alert team assessments.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
BACKGROUND: Telemedicine has created access to emergency stroke care for patients in all communities, regardless of geography. We hypothesized that there is no difference in speed of assessment between vascular neurologist (VN) robotic telepresence a...

Quantitative assessment of new MRI-based measurements to differentiate low and high stages of pelvic organ prolapse using support vector machines.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: The objective of this study was to quantitatively assess the ability of new MRI-based measurements to differentiate low and high stages of pelvic organ prolapse. New measurements representing pelvic structural characteris...

Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.

The Lancet. Respiratory medicine
BACKGROUND: Improved mortality prediction for patients in intensive care units is a big challenge. Many severity scores have been proposed, but findings of validation studies have shown that they are not adequately calibrated. The Super ICU Learner A...

Machine learning algorithms and forced oscillation measurements to categorise the airway obstruction severity in chronic obstructive pulmonary disease.

Computer methods and programs in biomedicine
The purpose of this study was to develop automatic classifiers to simplify the clinical use and increase the accuracy of the forced oscillation technique (FOT) in the categorisation of airway obstruction level in patients with chronic obstructive pul...

Robot-assisted gait training is not superior to balance training for improving postural instability in patients with mild to moderate Parkinson's disease: a single-blind randomized controlled trial.

Clinical rehabilitation
OBJECTIVE: The main aim was to compare robotic gait training vs. balance training for reducing postural instability in patients with Parkinson's disease. The secondary aim was to compare their effects on the level of confidence during activities of d...

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Cerebral cortex (New York, N.Y. : 1991)
Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associate...

Real-world effectiveness of cariprazine in major depressive disorder and bipolar I disorder in the United States.

Journal of medical economics
AIMS: The efficacy of cariprazine for major depressive disorder (MDD) (adjunctive therapy) and bipolar I (BP-I) depression has been demonstrated in clinical trials. This study evaluated the real-world effectiveness of cariprazine in reducing depressi...

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

Renal failure
OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model...

Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study.

The Journal of dermatological treatment
BACKGROUND: Identifying the risk of psoriasis relapse after discontinuing biologics can help optimize treatment strategies, potentially reducing relapse rates and alleviating the burden of disease management.