AIMC Topic: Machine Learning

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Learning from demonstration: Teaching a myoelectric prosthesis with an intact limb via reinforcement learning.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
Prosthetic arms should restore and extend the capabilities of someone with an amputation. They should move naturally and be able to perform elegant, coordinated movements that approximate those of a biological arm. Despite these objectives, the contr...
Electromyography Wearable Electronic Devices Humans Artificial Limbs Robotics Machine Learning Prosthesis Design Equipment Design Algorithms Arm Signal Processing, Computer-Assisted
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Representing high-dimensional data to intelligent prostheses and other wearable assistive robots: A first comparison of tile coding and selective Kanerva coding.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
Prosthetic devices have advanced in their capabilities and in the number and type of sensors included in their design. As the space of sensorimotor data available to a conventional or machine learning prosthetic control system increases in dimensiona...
Robotics Signal Processing, Computer-Assisted Artificial Limbs Prosthesis Design Software Algorithms Wearable Electronic Devices Exoskeleton Device Upper Extremity Humans Artificial Intelligence Machine Learning
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Adaptive learning to speed-up control of prosthetic hands: A few things everybody should know.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
Domain adaptation methods have been proposed to reduce the training efforts needed to control an upper-limb prosthesis by adapting well performing models from previous subjects to the new subject. These studies generally reported impressive reduction...
Machine Learning Algorithms Signal Processing, Computer-Assisted Electromyography Hand Amputees Artificial Limbs Humans
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Online sparse Gaussian process based human motion intent learning for an electrically actuated lower extremity exoskeleton.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
The most important step for lower extremity exoskeleton is to infer human motion intent (HMI), which contributes to achieve human exoskeleton collaboration. Since the user is in the control loop, the relationship between human robot interaction (HRI)...
Equipment Design Knee Joint Normal Distribution Movement Exoskeleton Device Self-Help Devices Humans Machine Learning Algorithms Lower Extremity
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Robotic learning from demonstration of therapist's time-varying assistance to a patient in trajectory-following tasks.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
The number of people with physical disabilities and impaired motion control is increasing. Consequently, there is a growing demand for intelligent assistive robotic systems to cooperate with people with disability and help them carry out different ta...
Humans Robotics Task Performance and Analysis Cerebral Palsy Machine Learning Self-Help Devices Algorithms Adult
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Automated stand-up and sit-down detection for robot-assisted body-weight support training with the FLOAT.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
Patients with impaired walking function are often dependent on assistive devices to retrain gait and regain independence in life. To provide adequate support, gait rehabilitation devices have to be manually set to the correct support mode or have to ...
Body Weight Neurological Rehabilitation Posture Robotics Pelvis Humans Machine Learning Algorithms Female Young Adult Adult Biomechanical Phenomena Male
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Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2017
OBJECTIVE: Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Soc...
Machine Learning Social Media Natural Language Processing Drug-Related Side Effects and Adverse Reactions Pharmacovigilance Humans Neural Networks, Computer
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Automated classification of eligibility criteria in clinical trials to facilitate patient-trial matching for specific patient populations.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2017
OBJECTIVE: To develop automated classification methods for eligibility criteria in ClinicalTrials.gov to facilitate patient-trial matching for specific populations such as persons living with HIV or pregnant women.
Datasets as Topic Clinical Trials as Topic Eligibility Determination HIV Seropositivity Neoplasms Natural Language Processing Patient Selection Humans Machine Learning
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Machine Learning Algorithms for Objective Remission and Clinical Outcomes with Thiopurines.

Journal of Crohn's & colitis Jul 1, 2017
BACKGROUND AND AIMS: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimising thiopurine therapy for inflammatory bowel disease [IBD] has proved difficult. Current methods u...
Retrospective Studies Female Hospitalization Young Adult Humans Machine Learning Algorithms Inflammatory Bowel Diseases Immunosuppressive Agents Area Under Curve Remission Induction Drug Prescriptions Azathioprine Mercaptopurine Adolescent Medication Adherence ROC Curve Treatment Outcome Adult Male Middle Aged
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Deep Learning in Mammography: Diagnostic Accuracy of a Multipurpose Image Analysis Software in the Detection of Breast Cancer.

Investigative radiology Jul 1, 2017
OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mammography d...
Reproducibility of Results Aged Aged, 80 and over Adult Machine Learning Retrospective Studies Female Image Processing, Computer-Assisted Follow-Up Studies Mammography Humans Breast Breast Neoplasms Middle Aged Prevalence ROC Curve
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