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Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients.

Clinical imaging
PURPOSE: To evaluate performance and the clinical impact of a novel machine learning based vessel-suppressing computer-aided detection (CAD) software in chest computed tomography (CT) of patients with malignant melanoma.

Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration.

IEEE journal of biomedical and health informatics
Deformable registration has been one of the pillars of biomedical image computing. Conventional approaches refer to the definition of a similarity criterion that, once endowed with a deformation model and a smoothness constraint, determines the optim...
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Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition.

IEEE journal of biomedical and health informatics
Multimodal medical image fusion, emerging as a hot topic, aims to fuse images with complementary multi-source information. In this paper, we propose a novel multimodal medical image fusion method based on structural patch decomposition (SPD) and fuzz...

HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders.

Genetics in medicine : official journal of the American College of Medical Genetics
Recent dramatic advances in multiomics research coupled with exponentially increasing volume, complexity, and interdisciplinary nature of publications are making it challenging for scientists to stay up-to-date on the literature. Strategies to addres...

Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning.

Surgical oncology
Glioblastoma multiforme (GBM) are aggressive brain tumors, which lead to poor overall survival (OS) of patients. OS prediction of GBM patients provides useful information for surgical and treatment planning. Radiomics research attempts at predicting ...

Digital Multiplierless Realization of Coupled Wilson Neuron Model.

IEEE transactions on biomedical circuits and systems
The human brain is composed of 10 neurons with a switching speed of about 1 ms. Studying spiking neural networks, including the modeling, simulation, and implementation of the biological neuron models, helps us to learn about the brain and the relate...

Fuzzy entropy based on differential evolution for breast gland segmentation.

Australasian physical & engineering sciences in medicine
For the diagnosis and treatment of breast tumors, the automatic detection of glands is a crucial step. The true segmentation of the gland is directly related to effective treatment effect of the patient. Therefore, it is necessary to propose an autom...

Identifying health information technology related safety event reports from patient safety event report databases.

Journal of biomedical informatics
OBJECTIVE: The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model featu...

Artificial intelligence: Implications for the health care risk manager?

Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management
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Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT.

Medical physics
BACKGROUND: Accurate prediction of radiation toxicity of healthy organs-at-risks (OARs) critically determines the radiation therapy (RT) success. The existing dose-volume histogram-based metric may grossly under/overestimate the therapeutic toxicity ...