AIMC Topic: Humans

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Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-FP-CIT indices.

Journal of neurology Apr 29, 2019
OBJECTIVES: To provide an automated classification method for degenerative parkinsonian syndromes (PS) based on semiquantitative I-FP-CIT SPECT striatal indices and support-vector-machine (SVM) analysis.
Iodine Radioisotopes Parkinsonian Disorders Corpus Striatum Tomography, Emission-Computed, Single-Photon Male Middle Aged Humans Support Vector Machine Aged Retrospective Studies Aged, 80 and over Female Adult
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Comedic experience with two robots aided a child with autism spectrum disorder to realize the importance of nonverbal communication.

Psychiatry and clinical neurosciences Apr 29, 2019
Facial Expression Interpersonal Relations Nonverbal Communication Wit and Humor as Topic Male Adolescent Robotics Humans Autism Spectrum Disorder
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Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders.

Computers in biology and medicine Apr 29, 2019
To estimate the reliability and cognitive states of operator performance in a human-machine collaborative environment, we propose a novel human mental workload (MW) recognizer based on deep learning principles and utilizing the features of the electr...
Cognition Models, Neurological Electroencephalography Humans Databases, Factual Deep Learning
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Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.

Nature neuroscience Apr 29, 2019
Non-recurrent deep convolutional neural networks (CNNs) are currently the best at modeling core object recognition, a behavior that is supported by the densely recurrent primate ventral stream, culminating in the inferior temporal (IT) cortex. If rec...
Neural Networks, Computer Animals Humans Recognition, Psychology Visual Perception Macaca mulatta Temporal Lobe
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Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

Medical physics Apr 29, 2019
PURPOSE: Accurate segmentation of rectal tumors is a basic and crucial task for diagnosis and treatment of rectal cancer. To avoid tedious manual delineation, an automatic rectal tumor segmentation model is proposed.
Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted Magnetic Resonance Imaging Rectal Neoplasms Humans
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Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.

EBioMedicine Apr 29, 2019
BACKGROUND: The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited s...
Models, Statistical Evolution, Molecular Antitubercular Agents Tuberculosis, Multidrug-Resistant Computational Biology Databases, Genetic Humans ROC Curve Reproducibility of Results Extensively Drug-Resistant Tuberculosis Cluster Analysis Machine Learning Genomics Microbial Sensitivity Tests Genetic Variation Prognosis Mycobacterium tuberculosis Genome, Bacterial
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Predicting coronary artery disease: a comparison between two data mining algorithms.

BMC public health Apr 29, 2019
BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data minin...
Coronary Artery Disease Data Mining Sex Factors Support Vector Machine Age Factors Predictive Value of Tests Electronic Health Records Female Risk Factors Male Humans ROC Curve Neural Networks, Computer Middle Aged Socioeconomic Factors Algorithms
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To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques.

Asian Pacific journal of cancer prevention : APJCP Apr 29, 2019
Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are proposed for mining the hidden pattern in the dataset. Ensemble-I and Ensemble- II both are machine learni...
Predictive Value of Tests Data Mining Thyroid Gland Humans Decision Support Systems, Clinical Neural Networks, Computer Algorithms Machine Learning Female
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Artificial Neural Network Analysis of Spontaneous Preterm Labor and Birth and Its Major Determinants.

Journal of Korean medical science Apr 29, 2019
BACKGROUND: Little research based on the artificial neural network (ANN) is done on preterm birth (spontaneous preterm labor and birth) and its major determinants. This study uses an ANN for analyzing preterm birth and its major determinants.
Neural Networks, Computer Pregnancy Female Infant, Newborn Humans ROC Curve Logistic Models Hypertension Diabetes Mellitus Premature Birth Risk Factors Adult Placenta Body Mass Index Gestational Age Obstetric Labor, Premature Cervix Uteri Area Under Curve
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Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics.

Physics in medicine and biology Apr 29, 2019
The use of treatment plan characteristics to predict patient-specific quality assurance (QA) measurement results has recently been reported as a strategy to help facilitate automated pre-treatment verification workflows or to provide a virtual assess...
Humans Radiotherapy Dosage Machine Learning Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Patient-Specific Modeling Particle Accelerators
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