AIMC Topic: False Positive Reactions

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A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Computer methods and programs in biomedicine Oct 5, 2018
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...
Humans Software Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Supervised Machine Learning RNA Pattern Recognition, Automated False Positive Reactions Breast Neoplasms Male Diagnosis, Computer-Assisted Deep Learning Lung Neoplasms Algorithms Female Reproducibility of Results Stomach Neoplasms
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Diagnosis of urinary tract infection based on artificial intelligence methods.

Computer methods and programs in biomedicine Oct 2, 2018
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflam...
Young Adult Adult Sensitivity and Specificity Male Middle Aged Machine Learning Algorithms Female Aged Support Vector Machine Decision Trees Urinary Tract Infections False Positive Reactions Cystitis Diagnosis, Computer-Assisted Adolescent Child ROC Curve Decision Support Systems, Clinical Humans Neural Networks, Computer Artificial Intelligence
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Is Multiclass Automatic Text De-Identification Worth the Effort?

Methods of information in medicine Sep 24, 2018
OBJECTIVES: Automatic de-identification to remove protected health information (PHI) from clinical text can use a "binary" model that replaces redacted text with a generic tag (e.g., ""), or can use a "multiclass" model that retains more class i...
False Positive Reactions Humans Algorithms Electronic Health Records Data Anonymization
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Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.

Computer methods and programs in biomedicine Aug 31, 2018
BACKGROUND AND OBJECTIVE: In pulmonary nodule detection, the first stage, candidate detection, aims to detect suspicious pulmonary nodules. However, detected candidates include many false positives and thus in the following stage, false positive redu...
Humans Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted False Positive Reactions Neural Networks, Computer Databases, Factual Tomography, X-Ray Computed Diagnosis, Computer-Assisted Lung Neoplasms
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CNN models discriminating between pulmonary micro-nodules and non-nodules from CT images.

Biomedical engineering online Jul 16, 2018
BACKGROUND: Early and automatic detection of pulmonary nodules from CT lung screening is the prerequisite for precise management of lung cancer. However, a large number of false positives appear in order to increase the sensitivity, especially for de...
Lung Image Processing, Computer-Assisted Lung Neoplasms False Positive Reactions Humans Neural Networks, Computer Databases, Factual Tomography, X-Ray Computed
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Chemical-induced disease relation extraction with dependency information and prior knowledge.

Journal of biomedical informatics Jul 11, 2018
Chemical-disease relation (CDR) extraction is significantly important to various areas of biomedical research and health care. Nowadays, many large-scale biomedical knowledge bases (KBs) containing triples about entity pairs and their relations have ...
Language Biomedical Research Computational Biology Models, Statistical Natural Language Processing Knowledge Bases Semantics False Positive Reactions Chemically-Induced Disorders Machine Learning Algorithms Research Design Databases, Factual Precision Medicine Humans Neural Networks, Computer
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A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases.

Computer methods and programs in biomedicine Jun 22, 2018
BACKGROUND AND OBJECTIVE: Drug-drug interaction (DDI) is one of the main causes of toxicity and treatment inefficacy. This work focuses on non-communicable diseases (NCDs), the non-transmissible and long-lasting diseases since they are the leading ca...
False Positive Reactions Quantitative Structure-Activity Relationship Computer Simulation Reproducibility of Results Support Vector Machine Cluster Analysis Area Under Curve Noncommunicable Diseases Drug Interactions Probability Cytochrome P-450 Enzyme System Simvastatin Humans Neural Networks, Computer Machine Learning Algorithms Databases, Factual
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Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Journal of clinical monitoring and computing May 24, 2018
Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most dangerous secondary insults and is related to poor outcome in patients. The overall aim of this stu...
Neural Networks, Computer Machine Learning Software Databases, Factual Prospective Studies Humans Young Adult Adult Sensitivity and Specificity Male Middle Aged Intensive Care Units Female Aged Aged, 80 and over Hypotension Critical Care False Positive Reactions Diagnosis, Computer-Assisted Brain Injuries Pilot Projects Adolescent Area Under Curve Brain Injuries, Traumatic Sample Size Bayes Theorem Signal Processing, Computer-Assisted
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Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction.

IEEE/ACM transactions on computational biology and bioinformatics May 21, 2018
Automatically extracting the relationships between chemicals and diseases is significantly important to various areas of biomedical research and health care. Biomedical experts have built many large-scale knowledge bases (KBs) to advance the developm...
Medical Subject Headings False Positive Reactions Myoclonus Databases, Factual Language Reproducibility of Results Inflammation Models, Statistical Myocardial Infarction Humans Thrombosis Neural Networks, Computer Knowledge Bases Machine Learning Data Mining Algorithms
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Localized instance fusion of MRI data of Alzheimer's disease for classification based on instance transfer ensemble learning.

Biomedical engineering online May 2, 2018
BACKGROUND: Diagnosis of Alzheimer's disease (AD) is very important, and MRI is an effective imaging mode of Alzheimer's disease. There are many existing studies on the diagnosis of Alzheimer's disease based on MRI data. However, there are no studies...
Humans Machine Learning Female Aged Aged, 80 and over Male Image Processing, Computer-Assisted Magnetic Resonance Imaging Alzheimer Disease False Positive Reactions
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