AIMC Topic: Humans

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Fully Automated Segmentation of Lower Extremity Deep Vein Thrombosis Using Convolutional Neural Network.

BioMed research international
OBJECTIVE: Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Accurate segmentation of DVT is important to facilitate the diagnosis and treatment. In the current study, we proposed a fully automatic method of DVT de...

Automated Bone Scan Index as an Imaging Biomarker to Predict Overall Survival in the Zometa European Study/SPCG11.

European urology oncology
BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostate cancer, it would be of value to use objective tools to monitor the status of bone metastases during clinical trials. Automated Bone Scan Index (aBSI...

Principal Component Analysis based on Nuclear norm Minimization.

Neural networks : the official journal of the International Neural Network Society
Principal component analysis (PCA) is a widely used tool for dimensionality reduction and feature extraction in the field of computer vision. Traditional PCA is sensitive to outliers which are common in empirical applications. Therefore, in recent ye...

Automatic annotation of surgical activities using virtual reality environments.

International journal of computer assisted radiology and surgery
PURPOSE: Annotation of surgical activities becomes increasingly important for many recent applications such as surgical workflow analysis, surgical situation awareness, and the design of the operating room of the future, especially to train machine l...

Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery.

International journal of medical informatics
BACKGROUND: Last-minute surgery cancellation represents a major wastage of resources and can cause significant inconvenience to patients. Our objectives in this study were: 1) To develop predictive models of last-minute surgery cancellation, utilizin...

A preoperative nomogram to predict major complications after robot assisted partial nephrectomy (UroCCR-57 study).

Urologic oncology
OBJECTIVE: To generate a nomogram based on preoperative parameters to predict the occurrence of a major complication within 30-days of robotic partial nephrectomy.

Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA.

Epidemics
Influenza is one of the main causes of death, not only in the USA but worldwide. Its significant economic and public health impacts necessitate development of accurate and efficient algorithms for forecasting of any upcoming influenza outbreaks. Most...

Slow cortical potential signal classification using concave-convex feature.

Journal of neuroscience methods
BACKGROUND: The classification of the slow cortical potential (SCP) signals plays a key role in a variety of research areas, including disease diagnostics, human-machine interaction, and education. The widely used classification methods, which combin...

Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks.

Neuroscience
Spatially separated brain areas interact with each other to form networks with coordinated activities, supporting various brain functions. Interaction structures among brain areas have been widely investigated through pairwise measures. However, inte...