AIMC Topic: Reproducibility of Results

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Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

BMC genomics Oct 18, 2016
BACKGROUND: Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheim...
Gene Expression Profiling Genetic Predisposition to Disease Genetic Association Studies Computational Biology Humans Machine Learning Reproducibility of Results Protein Interaction Mapping Alzheimer Disease Datasets as Topic Molecular Sequence Annotation Gene Ontology
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A machine learning tool for re-planning and adaptive RT: A multicenter cohort investigation.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Oct 17, 2016
PURPOSE: To predict patients who would benefit from adaptive radiotherapy (ART) and re-planning intervention based on machine learning from anatomical and dosimetric variations in a retrospective dataset.
Reproducibility of Results Cohort Studies Radiotherapy Planning, Computer-Assisted Humans Radiotherapy, Computer-Assisted Machine Learning Retrospective Studies
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ANN Prediction of Metabolic Syndrome: a Complex Puzzle that will be Completed.

Journal of medical systems Oct 11, 2016
The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabetes, cancers and chronic kidney disease. It would be very greatful that MetS diagnosis can be predic...
Humans Neural Networks, Computer Female Early Diagnosis Waist-Height Ratio Adult Male Middle Aged Adolescent Reproducibility of Results Blood Glucose Metabolic Syndrome Aged Genetic Predisposition to Disease Lipids Young Adult Body Mass Index Blood Pressure Age Factors Sex Factors
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Computer-aided diagnosis system for lung nodules based on computed tomography using shape analysis, a genetic algorithm, and SVM.

Medical & biological engineering & computing Oct 3, 2016
Lung cancer is the major cause of death among patients with cancer worldwide. This work is intended to develop a methodology for the diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LID...
Tomography, X-Ray Computed Female Reproducibility of Results Sensitivity and Specificity Humans Algorithms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Radiographic Image Enhancement Male Middle Aged Models, Genetic Support Vector Machine
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System Integration and In Vivo Testing of a Robot for Ultrasound Guidance and Monitoring During Radiotherapy.

IEEE transactions on bio-medical engineering Oct 3, 2016
We are developing a cooperatively controlled robot system for image-guided radiation therapy (IGRT) in which a clinician and robot share control of a 3-D ultrasound (US) probe. IGRT involves two main steps: 1) planning/simulation and 2) treatment del...
Systems Integration Robotics Equipment Design Ultrasonography, Interventional Dogs Humans Radiotherapy, Conformal Reproducibility of Results Equipment Failure Analysis Sensitivity and Specificity Radiotherapy, Image-Guided Animals Man-Machine Systems
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Outcome Prediction for Patient with High-Grade Gliomas from Brain Functional and Structural Networks.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
High-grade glioma (HGG) is a lethal cancer, which is characterized by very poor prognosis. To help optimize treatment strategy, accurate preoperative prediction of HGG patient's outcome (i.e., survival time) is of great clinical value. However, there...
Brain Neoplasms Brain Humans Treatment Outcome Retrospective Studies Glioma Machine Learning Neoplasm Grading Reproducibility of Results Magnetic Resonance Imaging Algorithms Connectome Sensitivity and Specificity Diffusion Tensor Imaging Life Expectancy
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Feature Selection Based on Iterative Canonical Correlation Analysis for Automatic Diagnosis of Parkinson's Disease.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
Parkinson's disease (PD) is a major progressive neurodegenerative disorder. Accurate diagnosis of PD is crucial to control the symptoms appropriately. However, its clinical diagnosis mostly relies on the subjective judgment of physicians and the clin...
Reproducibility of Results Sensitivity and Specificity Humans Neuroimaging Magnetic Resonance Imaging Algorithms Parkinson Disease Brain
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3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
High-grade glioma is the most aggressive and severe brain tumor that leads to death of almost 50% patients in 1-2 years. Thus, accurate prognosis for glioma patients would provide essential guidelines for their treatment planning. Conventional surviv...
Magnetic Resonance Imaging Multimodal Imaging Neoplasm Grading Life Expectancy Brain Neoplasms Brain Deep Learning Prognosis Glioma Reproducibility of Results Humans Sensitivity and Specificity Neural Networks, Computer Algorithms
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Early Diagnosis of Alzheimer's Disease by Joint Feature Selection and Classification on Temporally Structured Support Vector Machine.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
The diagnosis of Alzheimer's disease (AD) from neuroimaging data at the pre-clinical stage has been intensively investigated because of the immense social and economic cost. In the past decade, computational approaches on longitudinal image sequences...
Humans Algorithms Brain Reproducibility of Results Sensitivity and Specificity Disease Progression Cognitive Dysfunction Support Vector Machine Magnetic Resonance Imaging Alzheimer Disease Early Diagnosis
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Spatial Clockwork Recurrent Neural Network for Muscle Perimysium Segmentation.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Oct 2, 2016
Accurate segmentation of perimysium plays an important role in early diagnosis of many muscle diseases because many diseases contain different perimysium inflammation. However, it remains as a challenging task due to the complex appearance of the per...
Muscle Fibers, Skeletal Algorithms Reproducibility of Results Sensitivity and Specificity Muscle, Skeletal Humans Neural Networks, Computer
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