AIMC Topic: Humans

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Deep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis.

Multiple sclerosis (Houndmills, Basingstoke, England)
OBJECTIVE: The aim of this study is to assess the performance of deep learning convolutional neural networks (CNNs) in segmenting gadolinium-enhancing lesions using a large cohort of multiple sclerosis (MS) patients.

Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to build and train a deep convolutional neural networks (CNN) algorithm to segment muscular body mass (MBM) to predict muscular surface from a two-dimensional axial computed tomography (CT) slice through L3 vert...

Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity.

Progress in neurobiology
Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study t...

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

International journal of radiation oncology, biology, physics
PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic ...

Effect of Robot-Assisted Gait Training on Selective Voluntary Motor Control in Ambulatory Children with Cerebral Palsy.

Indian pediatrics
This pilot study investigated the efficacy of a four week robot-assisted gait training in twelve children with spastic diparesis. Short-term results and a 3-month follow-up showed statistically significantly increased selective motor control, walking...

Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.

Computer methods and programs in biomedicine
BACKGROUND: Intradialytic hypotension (IDH) is commonly occurred and links to higher mortality among patients undergoing hemodialysis (HD). Its early prediction and prevention will dramatically improve the quality of life. However, predicting the occ...

Performance improvement of mediastinal lymph node severity detection using GAN and Inception network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In lung cancer, the determination of mediastinal lymph node (MLN) status as benign or malignant influence treatment planning and survival rate. Invasive pathological tests for the classification of MLNs into benign and malig...

Evidence that the Kennedy and polyamine pathways are dysregulated in human brain in cases of dementia with Lewy bodies.

Brain research
Disruptions of brain metabolism are considered integral to the pathogenesis of dementia, but thus far little is known of how dementia with Lewy bodies (DLB) impacts the brain metabolome. DLB is less well known than other neurodegenerative diseases su...

The effects of different levels of realism on the training of CNNs with only synthetic images for the semantic segmentation of robotic instruments in a head phantom.

International journal of computer assisted radiology and surgery
PURPOSE: The manual generation of training data for the semantic segmentation of medical images using deep neural networks is a time-consuming and error-prone task. In this paper, we investigate the effect of different levels of realism on the traini...

Using artificial intelligence algorithms to identify existing knowledge within the back pain literature.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Artificial intelligence algorithms can now identify hidden data patterns within the scientific literature. In 2019, these algorithms identified a thermoelectric material within the pre-2009 chemistry literature; years before its discovery in...