AIMC Topic:
Databases, Factual
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Screening for active pulmonary tuberculosis: Development and applicability of artificial neural network models.
Tuberculosis (Edinburgh, Scotland)
May 19, 2018
Tuberculosis (TB) remains a significant public health challenge, motivated by the diversity of healthcare epidemiological settings, as other factors. Cost-effective screening has substantial importance for TB control, demanding new diagnostic tools. ...
Adult
Male
Middle Aged
Risk Assessment
Brazil
Lung
Prevalence
Diagnosis, Computer-Assisted
Female
Reproducibility of Results
Tuberculosis, Pulmonary
Risk Factors
Young Adult
Humans
Mycobacterium tuberculosis
Neural Networks, Computer
Bacteriological Techniques
Decision Support Systems, Clinical
Decision Support Techniques
Databases, Factual
Mass Screening
Predictive Value of Tests
Sputum
Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease.
American journal of physiology. Heart and circulatory physiology
May 18, 2018
Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. Using a novel bioinformatics text-mining tool, we studied six cate...
Phenotype Extraction Based on Word Embedding to Sentence Embedding Cascaded Approach.
IEEE transactions on nanobioscience
May 18, 2018
As a significant determinant in the development of named entity recognition, phenotypic descriptions are normally presented differently in biomedical literature with the use of complicated semantics. In this paper, a novel approach has been proposed ...
Assessment of the generalization of learned image reconstruction and the potential for transfer learning.
Magnetic resonance in medicine
May 17, 2018
PURPOSE: Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to asse...
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE transactions on medical imaging
May 17, 2018
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been th...
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification.
IEEE transactions on medical imaging
May 15, 2018
This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only image-level, semantic labels inste...
Cell dynamic morphology classification using deep convolutional neural networks.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
May 15, 2018
Cell morphology is often used as a proxy measurement of cell status to understand cell physiology. Hence, interpretation of cell dynamic morphology is a meaningful task in biomedical research. Inspired by the recent success of deep learning, we here ...
Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.
Computers in biology and medicine
May 12, 2018
MOTIVATION: The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of dee...
Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.
Journal of biomedical informatics
May 12, 2018
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches a...
Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers.
Artificial intelligence in medicine
May 10, 2018
OBJECTIVE: Death certificates are an invaluable source of cancer mortality statistics. However, this value can only be realised if accurate, quantitative data can be extracted from certificates-an aim hampered by both the volume and variable quality ...
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