AI Medical Compendium Topic:
Severity of Illness Index

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Identification of a Novel Clinical Phenotype of Severe Malaria using a Network-Based Clustering Approach.

Scientific reports
The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 400,000 deaths are reported every year, mainly in African children. The diversity of clinical presentations associated w...

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...

Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reason for admission, indication for delivery, optimal steroid use, gestational age, and other potential...

Minimally Invasive Surgical Approach for Posterior Tracheopexy to Treat Severe Tracheomalacia: Lessons Learned from Initial Case Series.

Journal of laparoendoscopic & advanced surgical techniques. Part A
Posterior tracheopexy directly addresses membranous tracheal intrusion in severe tracheomalacia (TM). We have previously reported our experience of posterior tracheopexy through open approach in a large series of patients. This study aimed to review...

Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...

Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED.

The American journal of emergency medicine
OBJECTIVE: The prediction of emergency department (ED) disposition at triage remains challenging. Machine learning approaches may enhance prediction. We compared the performance of several machine learning approaches for predicting two clinical outco...

Automated assessment of levodopa-induced dyskinesia: Evaluating the responsiveness of video-based features.

Parkinsonism & related disorders
INTRODUCTION: Technological solutions for quantifying Parkinson's disease (PD) symptoms may provide an objective means to track response to treatment, including side effects such as levodopa-induced dyskinesia. Vision-based systems are advantageous a...

Machine learning in cardiac CT: Basic concepts and contemporary data.

Journal of cardiovascular computed tomography
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular ...