AIMC Topic: Humans

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Machine learning concepts, concerns and opportunities for a pediatric radiologist.

Pediatric radiology Mar 29, 2019
Machine learning, a subfield of artificial intelligence, is a rapidly evolving technology that offers great potential for expanding the quality and value of pediatric radiology. We describe specific types of learning, including supervised, unsupervis...
Societies, Medical Radiology Quality Improvement Pediatrics Humans Machine Learning Patient Safety Diagnostic Errors
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Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach.

BMC medical research methodology Mar 29, 2019
BACKGROUND: Chronic respiratory symptoms involving bronchitis, cough and phlegm in children are underappreciated but pose a significant public health burden. Efforts for prevention and management could be supported by an understanding of the relative...
Nitrogen Dioxide Bronchitis, Chronic Cough Air Pollutants Environmental Exposure Child Longitudinal Studies Machine Learning Female Risk Factors Asthma Male Surveys and Questionnaires Humans
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Detection of movement onset using EMG signals for upper-limb exoskeletons in reaching tasks.

Journal of neuroengineering and rehabilitation Mar 29, 2019
BACKGROUND: To assist people with disabilities, exoskeletons must be provided with human-robot interfaces and smart algorithms capable to identify the user's movement intentions. Surface electromyographic (sEMG) signals could be suitable for this pur...
Humans Machine Learning Electromyography Movement Exoskeleton Device Female Adult Male Upper Extremity
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Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer.

Physics in medicine and biology Mar 29, 2019
Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential to optimizing treatment. Positron emission tomography (PET) and computed tomography (CT) imagi...
Humans Neural Networks, Computer Imaging, Three-Dimensional Lymphatic Metastasis Lymph Nodes Predictive Value of Tests Head and Neck Neoplasms Positron Emission Tomography Computed Tomography
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Breast cancer histopathological image classification using convolutional neural networks with small SE-ResNet module.

PloS one Mar 29, 2019
Although successful detection of malignant tumors from histopathological images largely depends on the long-term experience of radiologists, experts sometimes disagree with their decisions. Computer-aided diagnosis provides a second option for image ...
Humans Breast Neoplasms Neural Networks, Computer Image Processing, Computer-Assisted Molecular Imaging
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Information Theoretic Feature Transformation Learning for Brain Interfaces.

IEEE transactions on bio-medical engineering Mar 28, 2019
OBJECTIVE: A variety of pattern analysis techniques for model training in brain interfaces exploit neural feature dimensionality reduction based on feature ranking and selection heuristics. In the light of broad evidence demonstrating the potential s...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Adult Male Humans Electroencephalography Machine Learning Brain Algorithms Female Young Adult
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Computed Tomography-Based Radiomic Features Could Potentially Predict Microsatellite Instability Status in Stage II Colorectal Cancer: A Preliminary Study.

Academic radiology Mar 28, 2019
RATIONALE AND OBJECTIVES: To investigate whether quantitative radiomics features extracted from computed tomography (CT) can predict microsatellite instability (MSI) status in an Asian cohort of patients with stage Ⅱ colorectal cancer (CRC).
Neoplasm Staging Microsatellite Instability Middle Aged Colorectal Neoplasms ROC Curve Predictive Value of Tests Male Tomography, X-Ray Computed Female Humans Adult Machine Learning Retrospective Studies
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Learning mechanisms in cue reweighting.

Cognition Mar 28, 2019
Feedback has been shown to be effective in shifting attention across perceptual cues to a phonological contrast in speech perception (Francis, Baldwin & Nusbaum, 2000). However, the learning mechanisms behind this process remain obscure. We compare t...
Humans Computer Simulation Supervised Machine Learning Cues Psycholinguistics Speech Perception Feedback, Psychological Phonetics Reinforcement, Psychology
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Using automated computer vision and machine learning to code facial expressions of affect and arousal: Implications for emotion dysregulation research.

Development and psychopathology Mar 28, 2019
As early as infancy, caregivers' facial expressions shape children's behaviors, help them regulate their emotions, and encourage or dissuade their interpersonal agency. In childhood and adolescence, proficiencies in producing and decoding facial expr...
Mother-Child Relations Adolescent Child Emotions Software Female Affect Male Facial Expression Humans Arousal Machine Learning
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Building artificial intelligence-based personalized predictive models.

BJU international Mar 28, 2019
Precision Medicine Humans Artificial Intelligence
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