Neurology

Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case series.

RATIONALE: Computer-assisted detection (CAD) systems based on artificial intelligence (AI) using convolutional neural network (CNN) have been successfully used for the diagnosis of unruptured cerebral aneurysms in experimental situations. However, it is yet unclear whether CAD systems can detect cerebral aneurysms effectively in real-life clinical situations. This paper describes the diagnostic ef...

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning.

Many problems exist within the myriad of currently employed screening and diagnostic methods. Further, an incredibly wide variety of procedures are used to identify an even greater number of diseases which exist in the world. There is a definite unmet clinical need to improve diagnostic capabilities of these procedures, including improving test sensitivity and specificity, objectivity and definiti...

Voxel-based morphometry analysis and machine learning based classification in pediatric mesial temporal lobe epilepsy with hippocampal sclerosis.

Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is a common type of pediatric epilepsy. We sought to evaluate whether the combinati...

Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker.

The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging p...

Binary Classification of Alzheimer's Disease Using sMRI Imaging Modality and Deep Learning.

Alzheimer's disease (AD) is an irreversible devastative neurodegenerative disorder associated with progressive impairment of memory and cognitive func...

Computational framework for detection of subtypes of neuropsychiatric disorders based on DTI-derived anatomical connectivity.

Many brain disorders - such as Alzheimer's disease, Parkinson's disease, schizophrenia and autism - are heterogeneous, that is, they may have several ...

The human brain reveals resting state activity patterns that are predictive of biases in attitudes toward robots.

The increasing presence of robots in society necessitates a deeper understanding into what attitudes people have toward robots. People may treat robot...

[Study on the precision of the robot-assisted sacroiliac screw placement].

To evaluate the precision of the robot-assisted sacroiliac screw placement for posterior pelvis injury and the impacting factors. The clinical data ...

Identification of Diabetes Risk Factors in Chronic Cardiovascular Patients.

Specific predictive models for diabetes polyneuropathy based on screening methods, for example Nerve conduction studies (NCS, can reach up to AUC 65.8...

Pyramid-Shape Crossings and Intercrossing Fibers Are Key Elements for Construction of the Neural Network in the Superficial White Matter of the Human Cerebrum.

Structural analysis of the superficial white matter is prerequisite for the understanding of highly integrated functions of the human cerebral cortex....

[Successful Robotic Resection of Left Upper Mediastinal Tumor].

A man was diagnosed with a left upper mediastinal mass. The mass was located near the left subclavian vein, phrenic nerve, vagus nerve, left subclavia...

Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI).

This study aimed to diagnose the incidence of restless leg syndrome (RLS) in patients with diabetes mellitus (DM) type-2, thorough artificial intellig...

A new method to predict anomaly in brain network based on graph deep learning.

Functional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and dysfunction studies, has been improved in recent y...

Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Automatic segmentation of OARs based on convolutional ...

[Rapid screening and determination of fentanyl and its analogues in drugs by liquid chromatography- quadrupole time-of-flight mass spectrometry].

A method based on liquid chromatography coupled with high-resolution quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) was developed for the si...

A Unique Signature of Cardiac-Induced Cranial Forces During Acute Large Vessel Stroke and Development of a Predictive Model.

BACKGROUND: Cranial accelerometry is used to detect cerebral vasospasm and concussion. We explored this technique in a cohort of code stroke patients ...

Towards data-driven stroke rehabilitation via wearable sensors and deep learning.

Recovery after stroke is often incomplete, but rehabilitation training may potentiate recovery by engaging endogenous neuroplasticity. In preclinical ...

MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide.

Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological pro...

[Rehabilitation of traumatic spinal cord injury with lower limb exoskeleton].

In recent years, several technological innovations have emerged to improve the rehabilitation of traumatic spinal cord injury (SCI). Among them, robot...

Design and Validation of a Lower-Limb Haptic Rehabilitation Robot.

Present robots for investigating lower-limb motor control and rehabilitation focus on gait training. An alternative approach is to focus on restoring ...