AIMC Topic: Female

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Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach.

Translational psychiatry
Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psycholog...

A Predictive Model for Guillain-Barré Syndrome Based on Ensemble Methods.

Computational intelligence and neuroscience
Nowadays, Machine Learning methods have proven to be highly effective on the identification of various types of diseases, in the form of predictive models. Guillain-Barré syndrome (GBS) is a potentially fatal autoimmune neurological disorder that has...

Coarse-to-fine information integration in human vision.

NeuroImage
Coarse-to-fine theories of vision propose that the coarse information carried by the low spatial frequencies (LSF) of visual input guides the integration of finer, high spatial frequency (HSF) detail. Whether and how LSF modulates HSF processing in n...

Sensor Information Fusion by Integrated AI to Control Public Emotion in a Cyber-Physical Environment.

Sensors (Basel, Switzerland)
The cyber-physical system (CPS) is a next-generation smart system that combines computing with physical space. It has been applied in various fields because the uncertainty of the physical world can be ideally controlled using cyber technology. In te...

Unity and diversity in working memory load: Evidence for the separability of the executive functions updating and inhibition using machine learning.

Biological psychology
OBJECTIVE: According to current theoretical models of working memory (WM), executive functions (EFs) like updating, inhibition and shifting play an important role in WM functioning. The models state that EFs highly correlate with each other but also ...

The association between serum uric acid to creatinine ratio and renal disease progression in type 2 diabetic patients in Chinese communities.

Journal of diabetes and its complications
AIMS: Serum uric acid (UA) increases in patients with kidney disease due to the impaired UA clearance. The present study sought to evaluate the association between UA/creatinine ratio (UA/Cr) and renal disease progression in patients with type 2 diab...

Serum adipocytokines are associated with microalbuminuria in patients with type 1 diabetes and incipient chronic complications.

Diabetes & metabolic syndrome
AIMS: Recent studies have implicated possible contribution of adipocytokines in development and progression of microvascular complications in patients with type 1 diabetes (T1DM). The aim of our study was to investigate relationship between adipocyto...

Circulating betatrophin in relation to metabolic, inflammatory parameters, and oxidative stress in patients with type 2 diabetes mellitus.

Diabetes & metabolic syndrome
AIMS: Recently, it was suggested that betatrophin has a role in controlling pancreatic β cell proliferation and lipid metabolism, however, its role in human subjects has not been established yet. The predicting role of betatrophin and MDA along with ...

A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning.

Journal of medical systems
Skeletal bone age assessment is a widely used standard procedure in both disease detection and growth prediction for children in endocrinology. Conventional manual assessment methods mainly rely on personal experience in observing X-ray images of lef...

Using an artificial neural network to predict traumatic brain injury.

Journal of neurosurgery. Pediatrics
In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalization. A computational tool for ruling-in patients who will have clinically relevant TBI (CRTBI) would be valuable, providing an evidence-based mechanism...