AIMC Topic: Humans

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Structural characterization of the Extended Frontal Aslant Tract trajectory: A ML-validated laterality study in 3T and 7T.

NeuroImage
The Extended Frontal Aslant Tract (exFAT) is a recently described tractography-based extension of the Frontal Aslant Tract connecting Broca's territory to both supplementary and pre-supplementary motor areas, and more anterior prefrontal regions. In ...

Construction of gene-classifier and co-expression network analysis of genes in association with major depressive disorder.

Psychiatry research
Because the pathogenesis of major depressive disorder (MDD) is still unclear and the accurate diagnosis remains unavailable, we aimed to analyze its molecular mechanisms and develop a gene classifier to improve diagnostic accuracy. We extracted diffe...

The use of knowledge management tools in viroinformatics. Example study of a highly conserved sequence motif in Nsp3 of SARS-CoV-2 as a therapeutic target.

Computers in biology and medicine
Knowledge management tools that assist in systematic review and exploration of scientific knowledge generally are of obvious potential importance in evidence based medicine in general, but also to the design of therapeutics based on the protein subse...

There is No test-retest reliability of brain activation induced by robotic passive hand movement: A functional NIRS study.

Brain and behavior
INTRODUCTION: The basic paradigm of rehabilitation is based on the brain plasticity, and for promoting it, test-retest reliability (TRR) of brain activation in which certain area of the brain is repeatedly activated is required. In this study, we inv...

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor d...

Deep learning-based survival analysis for brain metastasis patients with the national cancer database.

Journal of applied clinical medical physics
PURPOSE: Prognostic indices such as the Brain Metastasis Graded Prognostic Assessment have been used in clinical settings to aid physicians and patients in determining an appropriate treatment regimen. These indices are derivative of traditional surv...

Variability and reproducibility in deep learning for medical image segmentation.

Scientific reports
Medical image segmentation is an important tool for current clinical applications. It is the backbone of numerous clinical diagnosis methods, oncological treatments and computer-integrated surgeries. A new class of machine learning algorithm, deep le...

Deep neural networks enable quantitative movement analysis using single-camera videos.

Nature communications
Many neurological and musculoskeletal diseases impair movement, which limits people's function and social participation. Quantitative assessment of motion is critical to medical decision-making but is currently possible only with expensive motion cap...

CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions.

Scientific reports
Cardiac CINE magnetic resonance imaging is the gold-standard for the assessment of cardiac function. Imaging accelerations have shown to enable 3D CINE with left ventricular (LV) coverage in a single breath-hold. However, 3D imaging remains limited t...