AI Medical Compendium Topic:
Case-Control Studies

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Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: We used artificial intelligence to develop a novel algorithm using physiomarkers to predict the onset of severe sepsis in critically ill children.

Statistical Learning Methods to Determine Immune Correlates of Herpes Zoster in Vaccine Efficacy Trials.

The Journal of infectious diseases
Using Super Learner, a machine learning statistical method, we assessed varicella zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA) antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Z...

Macular Vessel Density and Ganglion Cell/Inner Plexiform Layer Thickness and Their Combinational Index Using Artificial Intelligence.

Journal of glaucoma
PURPOSE: To evaluate the relationship between macular vessel density and ganglion cell to inner plexiform layer thickness (GCIPLT) and to compare their diagnostic performance. We attempted to develop a new combined parameter using an artificial neura...

Predictive markers of depression in hypertension.

Medicine
Hypertension and depression, as 2 major public health issues, are closely related. For patients having hypertension, in particular, depression is a risk factor for mortality and jeopardizes their wellbeing. The aim of the study is to apply support ve...

Classifying Treated vs. Untreated MDD Adolescents from Anatomical Connectivity using Nonlinear SVM.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Identification of the treatment-related responders for adolescent Major Depressive Disorder (MDD) is urgently needed to develop effective treatments. In this paper, machine learning based classifiers are used to reveal anatomical features as responde...

Multiobjective multifactor dimensionality reduction to detect SNP-SNP interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are popular markers for understanding disease susceptibility. Multifactor dimensionality reduction (MDR) can successfully detect considerable SSIs. Currently, MDR-based methods ...

Deep learning models to remix music for cochlear implant users.

The Journal of the Acoustical Society of America
The severe hearing loss problems that some people suffer can be treated by providing them with a surgically implanted electrical device called cochlear implant (CI). CI users struggle to perceive complex audio signals such as music; however, previous...

[A Paired Case Controlled Study Comparing the Short-term Outcomes of Da Vinci RATS and VATS Approach for Non-small Cell Lung Cancer].

Zhongguo fei ai za zhi = Chinese journal of lung cancer
BACKGROUND: Da Vinci Surgical System is one of the greatest inventions of the 20th century, which represents the development direction of the precise minimally invasive surgical techniques, the aim of this study was to comparing the short-term outcom...

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide ex...