AIMC Topic: Severity of Illness Index

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Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score.

JAMA neurology
IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings.

Diabetic macular edema grading in retinal images using vector quantization and semi-supervised learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Diabetic macular edema (DME) is one of the severe complication of diabetic retinopathy causing severe vision loss and leads to blindness in severe cases if left untreated.

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

Annals of the American Thoracic Society
RATIONALE: Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based o...

Procalcitonin in inflammatory bowel disease: Drawbacks and opportunities.

World journal of gastroenterology
The measurement of procalcitonin has recently become a mainstay for the diagnosis and therapeutic management of severe bacterial infections, especially those sustained by Gram-negative bacteria. Therefore, the aim of this article is to provide a narr...

Validation of Neutrophil CD64 Blood Biomarkers to Detect Mucosal Inflammation in Pediatric Crohn's Disease.

Inflammatory bowel diseases
BACKGROUND: In a pilot study, neutrophil CD64 surface expression was significantly elevated in newly diagnosed, pediatric-onset Crohn's disease. We aimed to test the CD64 biomarkers (neutrophil CD64 surface expression and soluble CD64) as determinate...