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A Comparative Study of Deep Learning Algorithms for Detecting Food Intake.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
The choice of appropriate machine learning algorithms is crucial for classification problems. This study compares the performance of state-of-the-art time-series deep learning algorithms for classifying food intake using sensor signals. The sensor si...
Algorithms Neural Networks, Computer Disease Progression Machine Learning Humans Deep Learning Eating
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Feasibility of a Deep Learning approach to estimate Shear Wave Speed using the framework of Reverberant Shear Wave Elastography: A numerical simulation study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Reverberant Shear Wave Elastography (RSWE) is an ultrasound elastography technique that offers great advantages, however, current estimators generate underestimations and time-consuming issues. As well, the involvement of Deep Learning into the medic...
Elasticity Imaging Techniques Computer Simulation Female Humans Feasibility Studies Phantoms, Imaging Male Deep Learning
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A Generic Semi-Supervised and Active Learning Framework for Biomedical Text Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Biomedical text classification requires having training examples labeled by clinical specialists, a process that can be costly. To address this problem, active learning incrementally selects a subset of the most informative unlabeled examples, sample...
Obesity Supervised Machine Learning Smoking Problem-Based Learning Humans Algorithms
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CNN-LSTM Based Multimodal MRI and Clinical Data Fusion for Predicting Functional Outcome in Stroke Patients.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Clinical outcome prediction plays an important role in stroke patient management. From a machine learning point-of-view, one of the main challenges is dealing with heterogeneous data at patient admission, i.e. the image data which are multidimensiona...
Stroke Records United States Humans Magnetic Resonance Imaging Neural Networks, Computer
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Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more favourable outcome. Once detected, grading IPMNs accurately is also nec...
Pancreatic Intraductal Neoplasms Electric Power Supplies Records Magnetic Resonance Imaging Humans Artificial Intelligence
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Novel Insights on Induced Sparsity in Multi-Time Attention Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Current deep learning approaches for dealing with sparse irregularly sampled time-series data do not exploit the extent of sparsity of the input data. Our work is inspired by the sparse and irregularly sampled nature of physiological time series data...
Electronic Health Records Humans Neural Networks, Computer Algorithms
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A streamable large-scale clinical EEG dataset for Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Deep Learning has revolutionized various fields, including Computer Vision, Natural Language Processing, as well as Biomedical research. Within the field of neuroscience, specifically in electrophysiological neuroimaging, researchers are starting to ...
Humans Brain Electroencephalography Neurosciences Biomedical Research Deep Learning
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Analysis of Current Deep Learning Networks for Semantic Segmentation of Anatomical Structures in Laparoscopic Surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Semantic segmentation of anatomical structures in laparoscopic videos is a crucial task to enable the development of new computer-assisted systems that can assist surgeons during surgery. However, this is a difficult task due to artifacts and similar...
Laparoscopy Cholecystectomy, Laparoscopic Semantics Surgeons Deep Learning Humans
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A Lymphatic Drainage Robot for Lymphedema Rehabilitation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Lymphedema is a medical condition that results in swelling and discomfort in human arms or legs. Caused due to the build-up of lymph fluid in the tissues under the skin, lymphedema commonly affects one of the arms or legs and it is an incurable condi...
Leg Lymphatic Vessels Medicine Robotics Lymphedema Humans
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Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Deep neural networks (DNNs) are the primary driving force for the current development of medical imaging analysis tools and often provide exciting performance on various tasks. However, such results are usually reported on the overall performance of ...
Diagnostic Imaging Uncertainty Neural Networks, Computer
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