AIMC Topic: Humans

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A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning.

Medical image analysis Mar 22, 2019
In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation...
Organs at Risk Image Processing, Computer-Assisted Humans Radiotherapy Planning, Computer-Assisted Magnetic Resonance Imaging Glioblastoma Neural Networks, Computer Brain Neoplasms
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BIRNet: Brain image registration using dual-supervised fully convolutional networks.

Medical image analysis Mar 22, 2019
In this paper, we propose a deep learning approach for image registration by predicting deformation from image appearance. Since obtaining ground-truth deformation fields for training can be challenging, we design a fully convolutional network that i...
Magnetic Resonance Imaging Brain Mapping Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted
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Baseball Player Behavior Classification System Using Long Short-Term Memory with Multimodal Features.

Sensors (Basel, Switzerland) Mar 22, 2019
In this paper, a preliminary baseball player behavior classification system is proposed. By using multiple IoT sensors and cameras, the proposed method accurately recognizes many of baseball players' behaviors by analyzing signals from heterogeneous ...
Humans Neural Networks, Computer Joints Photography Behavior Baseball Deep Learning Wearable Electronic Devices Accelerometry
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Predicting factors for survival of breast cancer patients using machine learning techniques.

BMC medical informatics and decision making Mar 22, 2019
BACKGROUND: Breast cancer is one of the most common diseases in women worldwide. Many studies have been conducted to predict the survival indicators, however most of these analyses were predominantly performed using basic statistical methods. As an a...
Humans Adult Breast Neoplasms Middle Aged Support Vector Machine Neural Networks, Computer Prognosis Female Decision Trees
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LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features.

BMC cancer Mar 22, 2019
BACKGROUND: Lung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction...
Adenocarcinoma of Lung Models, Biological Survival Analysis Datasets as Topic ROC Curve Prognosis Survival Rate Lung Neoplasms Humans Biomarkers, Tumor Genomics Precision Medicine Computational Biology Support Vector Machine Mutation Feasibility Studies
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Hippocampus Segmentation Based on Iterative Local Linear Mapping With Representative and Local Structure-Preserved Feature Embedding.

IEEE transactions on medical imaging Mar 21, 2019
Hippocampus segmentation plays a significant role in mental disease diagnoses, such as Alzheimer's disease, epilepsy, and so on. Patch-based multi-atlas segmentation (PBMAS) approach is a popular method for hippocampus segmentation and has achieved a...
Hippocampus Neuroimaging Magnetic Resonance Imaging Alzheimer Disease Image Interpretation, Computer-Assisted Humans Algorithms Deep Learning
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Arterial Spin Labeling Images Synthesis From sMRI Using Unbalanced Deep Discriminant Learning.

IEEE transactions on medical imaging Mar 21, 2019
Adequate medical images are often indispensable in contemporary deep learning-based medical imaging studies, although the acquisition of certain image modalities may be limited due to several issues including high costs and patients issues. However, ...
Brain Aged Middle Aged Deep Learning Dementia Magnetic Resonance Imaging Humans Image Interpretation, Computer-Assisted Spin Labels
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Enhancer prediction with histone modification marks using a hybrid neural network model.

Methods (San Diego, Calif.) Mar 21, 2019
Enhancer is a DNA sequence of a genome that controls transcription of downstream target genes. Enhancers are known to be associated with certain epigenetic signatures. Machine learning tools, such as CSI-ANN, ChromHMM, and RFECS, were developed for p...
Epigenomics Histones Enhancer Elements, Genetic Neural Networks, Computer Chromatin Machine Learning Histone Code Humans Computational Biology
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Biochemical, machine learning and molecular approaches for the differential diagnosis of Mucopolysaccharidoses.

Molecular and cellular biochemistry Mar 21, 2019
This study was aimed to construct classification and regression tree (CART) model of glycosaminoglycans (GAGs) for the differential diagnosis of Mucopolysaccharidoses (MPS). Two-dimensional electrophoresis and liquid chromatography-tandem mass spectr...
Chondroitinsulfatases Iduronidase Acetylglucosaminidase Hydrolases Mucopolysaccharidoses Child Chromatography, Liquid Diagnosis, Differential Humans Mutation Tandem Mass Spectrometry Machine Learning Glycosaminoglycans Infant Adolescent Child, Preschool Female Adult Male
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Swarm-Fuzzy Rule-Based Targeted Nano Delivery Using Bioinspired Nanomachines.

IEEE transactions on nanobioscience Mar 21, 2019
Cooperative navigation and swarm decision making take center stage in a broad range of distributed applications with high-environmental and measurement uncertainties. Here, we propose a fuzzy carotid body-inspired nanonetwork (FCBN) of autonomous nan...
Algorithms Drug Delivery Systems Neoplasms Humans Fuzzy Logic Carotid Body Models, Biological Nanomedicine
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