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Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results.

Japanese journal of radiology
PURPOSE: To evaluate whether early chest computed tomography (CT) lesions quantified by an artificial intelligence (AI)-based commercial software and blood test values at the initial presentation can differentiate the severity of COVID-19 pneumonia.

EEG microstate features for schizophrenia classification.

PloS one
Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes ...

Artificial intelligence for classifying uncertain images by humans in determining choroidal vascular running pattern and comparisons with automated classification between artificial intelligence.

PloS one
PURPOSE: Abnormalities of the running pattern of choroidal vessel have been reported in eyes with pachychoroid diseases. However, it is difficult for clinicians to judge the running pattern with high reproducibility. Thus, the purpose of this study w...

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.

Nutrients
The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose l...

Prediction of premature all-cause mortality in patients receiving peritoneal dialysis using modified artificial neural networks.

Aging
Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate and early prediction of mortality is critical and difficult. Three prediction models, the logistic regression (LR) model, artificial neural network (AN...

Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma.

Scientific reports
Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promisi...

Prediction of functional outcomes of schizophrenia with genetic biomarkers using a bagging ensemble machine learning method with feature selection.

Scientific reports
Genetic variants such as single nucleotide polymorphisms (SNPs) have been suggested as potential molecular biomarkers to predict the functional outcome of psychiatric disorders. To assess the schizophrenia' functional outcomes such as Quality of Life...

Generalizable dimensions of human cortical auditory processing of speech in natural soundscapes: A data-driven ultra high field fMRI approach.

NeuroImage
Speech comprehension in natural soundscapes rests on the ability of the auditory system to extract speech information from a complex acoustic signal with overlapping contributions from many sound sources. Here we reveal the canonical processing of sp...

Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.

Clinical radiology
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...