AIMC Topic: Humans

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Robot assisted training for the upper limb after stroke (RATULS): a multicentre randomised controlled trial.

Lancet (London, England) May 22, 2019
BACKGROUND: Loss of arm function is a common problem after stroke. Robot-assisted training might improve arm function and activities of daily living. We compared the clinical effectiveness of robot-assisted training using the MIT-Manus robotic gym wi...
Humans Female Middle Aged Stroke Rehabilitation Treatment Outcome Robotics Recovery of Function United Kingdom Upper Extremity Aged Male
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Robotic-assisted training after stroke: RATULS advances science.

Lancet (London, England) May 22, 2019
Stroke Upper Extremity Robotics Robotic Surgical Procedures Humans
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Towards the automated economic assessment of newborn screening for rare diseases.

Journal of biomedical informatics May 22, 2019
OBJECTIVE: Economic assessments of newborn screening programs for rare diseases involve the use of models and require huge efforts to synthesize information from different sources. Sharing and automatically or semi-automatically reusing this informat...
Rare Diseases Biological Ontologies Neonatal Screening Humans Databases, Factual Infant, Newborn Cost-Benefit Analysis Computer Simulation
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Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments.

Journal of chemical information and modeling May 22, 2019
Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules is so vast that only a limited exploration with the traditional methods can be ever possible. ...
Humans Machine Learning Robotics Tungsten Compounds Computational Chemistry Inorganic Chemicals Models, Chemical Crystallization
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Extract Features from Periocular Region to Identify the Age Using Machine Learning Algorithms.

Journal of medical systems May 22, 2019
Latest studies done on huge data collected from aging features proved that the performance of facial image based age estimation is low and need to be improved. One of the significant biometric traits for human recognition or search is Human age. Age ...
Humans Machine Learning Pattern Recognition, Automated Biometry Eye Algorithms Aging
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Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides.

Journal for immunotherapy of cancer May 22, 2019
BACKGROUND: Targeting epitopes derived from neo-antigens (or "neo-epitopes") represents a promising immunotherapy approach with limited off-target effects. However, most peptides predicted using MHC binding prediction algorithms do not induce a CD8 +...
Immunotherapy Epitopes, T-Lymphocyte Mutation Lymphocyte Activation Oligopeptides Protein Binding Humans Machine Learning
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See your mental state from your walk: Recognizing anxiety and depression through Kinect-recorded gait data.

PloS one May 22, 2019
As the challenge of mental health problems such as anxiety and depression increasing today, more convenient, objective, real-time assessing techniques of mental state are in need. The Microsoft Kinect camera is a possible option for contactlessly cap...
Walking Gait Depressive Disorder Algorithms Surveys and Questionnaires Psychological Tests Young Adult Humans Female Models, Statistical Male Adult Mental Health Machine Learning Anxiety Disorders
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Machine learning's feet of clay.

Journal of evaluation in clinical practice May 21, 2019
Machine Learning Clay Humans Artificial Intelligence
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Does transanal total mesorectal excision of rectal cancer improve histopathology metrics and/or complication rates? A meta-analysis.

Surgical oncology May 21, 2019
BACKGROUND: The aim of this meta-analysis was to determine whether transanal total mesorectal excision (taTME) improves histopathology metrics and/or complication rates when compared to robotic total mesorectal excision (R-TME) of resectable rectal c...
Postoperative Complications Treatment Outcome Robotics Transanal Endoscopic Surgery Humans Laparoscopy Rectal Neoplasms
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Learning, planning, and control in a monolithic neural event inference architecture.

Neural networks : the official journal of the International Neural Network Society May 21, 2019
We introduce REPRISE, a REtrospective and PRospective Inference SchEme, which learns temporal event-predictive models of dynamical systems. REPRISE infers the unobservable contextual event state and accompanying temporal predictive models that best e...
Machine Learning Learning Models, Neurological Humans
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