AIMC Topic: Humans

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AEB effectiveness evaluation based on car-to-cyclist accident reconstructions using video of drive recorder.

Traffic injury prevention Mar 1, 2019
OBJECTIVE: Though autonomous emergency braking (AEB) systems for car-to-cyclist collisions have been under development, an estimate of the benefit of AEB systems based on an analysis of accident data is needed for further enhancing their development....
Automobiles Accidents, Traffic Humans Automation Artificial Intelligence Protective Devices Deceleration
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Deep learning for predicting toxicity of chemicals: a mini review.

Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews Mar 1, 2019
Humans and wildlife inhabit a world with panoply of natural and synthetic chemicals. Alarmingly, only a limited number of chemicals have undergone comprehensive toxicological evaluation due to limitations of traditional toxicity testing. High-through...
High-Throughput Screening Assays Quantitative Structure-Activity Relationship Toxicity Tests Deep Learning Humans Models, Chemical Neural Networks, Computer Environmental Pollutants Machine Learning
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Classifying Biomedical Figures by Modality via Multi-Label Learning.

IEEE journal of biomedical and health informatics Feb 28, 2019
The figures found in biomedical literature are a vital part of biomedical research, education, and clinical decision. The multitude of their modalities and the lack of corresponding metadata constitute search and information, retrieval a difficult ta...
Information Storage and Retrieval Image Processing, Computer-Assisted Diagnostic Imaging Data Mining Image Interpretation, Computer-Assisted Humans Machine Learning Algorithms
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Model-based hearing diagnostics based on wideband tympanometry measurements utilizing fuzzy arithmetic.

Hearing research Feb 28, 2019
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves, that represent the statistical range of normal hearing responses. Because of large inter-individual variances in...
Ligaments Tympanic Membrane Ear, Middle Acoustic Impedance Tests Ear Ossicles Humans Ear Diseases Ear Canal Cluster Analysis Predictive Value of Tests Hearing Joints Reproducibility of Results Models, Theoretical Fuzzy Logic
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Bone texture analysis for prediction of incident radiographic hip osteoarthritis using machine learning: data from the Cohort Hip and Cohort Knee (CHECK) study.

Osteoarthritis and cartilage Feb 28, 2019
OBJECTIVE: To assess the ability of radiography-based bone texture variables in proximal femur and acetabulum to predict incident radiographic hip osteoarthritis (rHOA) over a 10 years period.
Femur Osteoarthritis, Hip Fractals Osteophyte Radiography Netherlands Arthroplasty, Replacement, Hip Incidence Cohort Studies ROC Curve Acetabulum Area Under Curve Image Processing, Computer-Assisted Body Mass Index Female Male Middle Aged Humans Machine Learning Prospective Studies
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Scoring upper-extremity motor function from EEG with artificial neural networks: a preliminary study.

Journal of neural engineering Feb 28, 2019
OBJECTIVE: Motor function of chronic stroke survivors is generally accessed using clinical motor assessments. These motor assessments are partially subjective and require prior training for the examiners. Additionally, those motor function assessment...
Stroke Rehabilitation Electroencephalography Stroke Upper Extremity Female Aged Aged, 80 and over Middle Aged Recovery of Function Adult Male Humans Neural Networks, Computer Brain
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An integrative computational architecture for object-driven cortex.

Current opinion in neurobiology Feb 28, 2019
Computational architecture for object-driven cortex Objects in motion activate multiple cortical regions in every lobe of the human brain. Do these regions represent a collection of independent systems, or is there an overarching functional architect...
Humans Neural Networks, Computer Brain Recognition, Psychology Artificial Intelligence Algorithms
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U-Net based deep learning bladder segmentation in CT urography.

Medical physics Feb 28, 2019
OBJECTIVES: To develop a U-Net-based deep learning approach (U-DL) for bladder segmentation in computed tomography urography (CTU) as a part of a computer-assisted bladder cancer detection and treatment response assessment pipeline.
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Urinary Bladder Neoplasms Urinary Bladder Urography Tomography, X-Ray Computed Case-Control Studies Deep Learning
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Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis.

Trends in cancer Feb 28, 2019
Deep learning refers to a set of computer models that have recently been used to make unprecedented progress in the way computers extract information from images. These algorithms have been applied to tasks in numerous medical specialties, most exten...
Humans Neural Networks, Computer Artificial Intelligence Machine Learning Image Processing, Computer-Assisted Workflow Immunohistochemistry Tomography, X-Ray Computed Neoplasms Deep Learning
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Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning.

AJNR. American journal of neuroradiology Feb 28, 2019
BACKGROUND AND PURPOSE: MR imaging-based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a tran...
Aged Adult Brain Neoplasms Male Humans Machine Learning Female Neuroimaging Middle Aged Magnetic Resonance Imaging Glioblastoma
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