AIMC Topic: Adult

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Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks.

Artificial intelligence in medicine
Manual annotation is considered to be the "gold standard" in medical imaging analysis. However, medical imaging datasets that include expert manual segmentation are scarce as this step is time-consuming, and therefore expensive. Moreover, single-rate...

Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.

International journal of radiation oncology, biology, physics
PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of great help in glioma management. This study aimed to create a highly accurate machine learning model to perform glioma grading.

Novel relative relevance score for estimating brain connectivity from fMRI data using an explainable neural network approach.

Journal of neuroscience methods
BACKGROUND: Functional integration or connectivity in brain is directional, non-linear as well as variable in time-lagged dependence. Deep neural networks (DNN) have become an indispensable tool everywhere, by learning higher levels of abstract and c...

Energy-Efficient Intelligent ECG Monitoring for Wearable Devices.

IEEE transactions on biomedical circuits and systems
Wearable intelligent ECG monitoring devices can perform automatic ECG diagnosis in real time and send out alert signal together with abnormal ECG signal for doctor's further analysis. This provides a means for the patient to identify their heart prob...

Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice.

Neurorehabilitation and neural repair
. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor improvement has been shown at the joints trained, but generalization to real-world function has not ...

Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: As the most commonly occurring form of mental illness worldwide, depression poses significant health and economic burdens to both the individual and community. Different types of depression pose different levels of risk. Individuals who s...

Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach.

BMC infectious diseases
BACKGROUND: Despite the greater sensitivity of the new dengue clinical classification proposed by the World Health Organization (WHO) in 2009, there is a need for a better definition of warning signs and clinical progression of dengue cases. Classic ...

Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures.

PloS one
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in...

Artificial neural networks accurately predict intra-abdominal infection in moderately severe and severe acute pancreatitis.

Journal of digestive diseases
OBJECTIVE: The aim of this study was to evaluate the efficacy of artificial neural networks (ANN) in predicting intra-abdominal infection in moderately severe (MASP) and severe acute pancreatitis (SAP) compared with that of a logistic regression mode...