AIMC Topic: Machine Learning

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Comparison of Machine Learning Techniques for Activities of Daily Living Classification with Electromyographic Data.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Advances in data science and wearable robotic devices present an opportunity to improve rehabilitation outcomes. Some of these devices incorporate electromyography (EMG) electrodes that sense physiological patient activity, making it possible to deve...

[Research on grading prediction model of traumatic hemorrhage volume based on deep learning].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To develop a grading prediction model of traumatic hemorrhage volume based on deep learning and assist in predicting traumatic hemorrhage volume.

Hospital-Agnostic Image Representation Learning in Digital Pathology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sites gives rise to variability in the histopathology images, thus making consistent diagnosis challeng...

The Use of Datasets of Bad Quality Images to Define Fundus Image Quality.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Screening programs for sight-threatening diseases rely on the grading of a large number of digital retinal images. As automatic image grading technology evolves, there emerges a need to provide a rigorous definition of image quality with reference to...

Addressing the Intra-class Mode Collapse Problem using Adaptive Input Image Normalization in GAN-based X-ray Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adversarial Networks play a key role in addressing this imbalance by enabling the generation of synthetic images to augment datasets. It is important to ge...

Stressalyzer: Convolutional Neural Network Framework for Personalized Stress Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Stress detection and monitoring is an active area of research with important implications for an individual's personal, professional, and social health. Current approaches for stress classification use traditional machine learning algorithms trained ...

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep learning algorithms for predicting from neuroimaging data have shown considerable promise. Deep learning models that take advantage of the data's 3D structure have been proven to outperform ordinary machine learning on a number of learning tasks...

Cross-Validation of Machine Learning Models for the Functional Outcome Prediction after Post-Stroke Robot-Assisted Rehabilitation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The state of the art is still lacking an extensive analysis of which clinical characteristics are leading to better outcomes after robot-assisted rehabilitation on post-stroke patients. Prognostic machine learning-based models could promote the ident...

Sequential Learning on sEMGs in Short- and Long-term Situations via Self-training Semi-supervised Support Vector Machine.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The purpose of this study it to assess the effect of sequential learning of self-training support vector machine (ST-S3VM) on short- and long-term surface electromyogram (sEMG) datasets. A machine learning-based supervised classi-fier is enabling sta...

Deep Feature Fusion via Graph Convolutional Network for Intracranial Artery Labeling.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Intracranial arteries are critical blood vessels that supply the brain with oxygenated blood. Intracranial artery labels provide valuable guidance and navigation to numerous clinical applications and disease diagnoses. Various machine learning algori...