AI Medical Compendium Topic:
Area Under Curve

Clear Filters Showing 851 to 860 of 1160 articles

Predicting posttraumatic stress disorder following a natural disaster.

Journal of psychiatric research
Earthquakes are a common and deadly natural disaster, with roughly one-quarter of survivors subsequently developing posttraumatic stress disorder (PTSD). Despite progress identifying risk factors, limited research has examined how to combine variable...

Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index.

Annals of emergency medicine
STUDY OBJECTIVE: Standards for emergency department (ED) triage in the United States rely heavily on subjective assessment and are limited in their ability to risk-stratify patients. This study seeks to evaluate an electronic triage system (e-triage)...

Gene2DisCo: Gene to disease using disease commonalities.

Artificial intelligence in medicine
OBJECTIVE: Finding the human genes co-causing complex diseases, also known as "disease-genes", is one of the emerging and challenging tasks in biomedicine. This process, termed gene prioritization (GP), is characterized by a scarcity of known disease...

A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Scientific reports
Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, ...

Reconstructing Genetic Regulatory Networks Using Two-Step Algorithms with the Differential Equation Models of Neural Networks.

Interdisciplinary sciences, computational life sciences
BACKGROUND: The identification of genetic regulatory networks (GRNs) provides insights into complex cellular processes. A class of recurrent neural networks (RNNs) captures the dynamics of GRN. Algorithms combining the RNN and machine learning scheme...

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks.

PloS one
Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proacti...

Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest.

International journal of molecular sciences
Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortmen...

Development of machine learning models for diagnosis of glaucoma.

PloS one
The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features fro...