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Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.
Journal of magnetic resonance imaging : JMRI
Sep 25, 2018
BACKGROUND: A current challenge in osteoporosis is identifying patients at risk of bone fracture.
Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images.
European radiology
Sep 25, 2018
OBJECTIVES: To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.
A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson's disease.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Sep 25, 2018
OBJECTIVE: This study seeks to systematically review the selection of features and algorithms for machine learning and automation in deep brain stimulation surgery (DBS) for Parkinson's disease. This will assist in consolidating current knowledge and...
Gene ontology enrichment analysis of congenital diaphragmatic hernia-associated genes.
Pediatric research
Sep 25, 2018
Congenital diaphragmatic hernia (CDH) is a commonly occurring major congenital anomaly with a profound impact on neonatal mortality. The etiology of CDH is poorly understood and is complicated by multiple clinical presentations, reflecting the locati...
Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.
Radiology
Sep 25, 2018
Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For ...
Deep learning with convolutional neural network for objective skill evaluation in robot-assisted surgery.
International journal of computer assisted radiology and surgery
Sep 25, 2018
PURPOSE: With the advent of robot-assisted surgery, the role of data-driven approaches to integrate statistics and machine learning is growing rapidly with prominent interests in objective surgical skill assessment. However, most existing work requir...
A Convolutional Neural Network Uses Microscopic Images to Differentiate between Mouse and Human Cell Lines and Their Radioresistant Clones.
Cancer research
Sep 25, 2018
: Artificial intelligence (AI) trained with a convolutional neural network (CNN) is a recent technological advancement. Previously, several attempts have been made to train AI using medical images for clinical applications. However, whether AI can di...
Predicting of anaphylaxis in big data EMR by exploring machine learning approaches.
Journal of biomedical informatics
Sep 25, 2018
Anaphylaxis is a life-threatening allergic reaction that occurs suddenly after contact with an allergen. Epidemiological studies about anaphylaxis are very important in planning and evaluating new strategies that prevent this reaction, but also in pr...
Using Artificial Intelligence (Watson for Oncology) for Treatment Recommendations Amongst Chinese Patients with Lung Cancer: Feasibility Study.
Journal of medical Internet research
Sep 25, 2018
BACKGROUND: Artificial intelligence (AI) is developing quickly in the medical field and can benefit both medical staff and patients. The clinical decision support system Watson for Oncology (WFO) is an outstanding representative AI in the medical fie...
Feasibility Study of Advanced Neural Networks Applied to sEMG-Based Force Estimation.
Sensors (Basel, Switzerland)
Sep 25, 2018
To find out the feasibility of different neural networks in sEMG-based force estimation, in this paper, three types of networks, namely convolutional neural network (CNN), long short-term memory (LSTM) network and their combination (C-LSTM) were appl...
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