AIMC Topic: Data Mining

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Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes.

Yearbook of medical informatics Aug 16, 2019
OBJECTIVE: To select, present, and summarize the best papers published in 2018 in the field of Knowledge Representation and Management (KRM).
Big Data Genomics Genetic Association Studies Artificial Intelligence Data Analysis Deep Learning Biological Ontologies Knowledge Management Computational Biology Data Mining Semantics
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A Lightweight API-Based Approach for Building Flexible Clinical NLP Systems.

Journal of healthcare engineering Aug 15, 2019
Natural language processing (NLP) has become essential for secondary use of clinical data. Over the last two decades, many clinical NLP systems were developed in both academia and industry. However, nearly all existing systems are restricted to speci...
False Positive Reactions Natural Language Processing Databases, Factual Pharmaceutical Preparations Data Mining Humans Patient Discharge Medical Informatics Reproducibility of Results Machine Learning Clinical Trials as Topic Obesity
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Clustering-based undersampling with random over sampling examples and support vector machine for imbalanced classification of breast cancer diagnosis.

Computer assisted surgery (Abingdon, England) Aug 12, 2019
To overcome the two-class imbalanced classification problem existing in the diagnosis of breast cancer, a hybrid of Random Over Sampling Example, K-means and Support vector machine (RK-SVM) model is proposed which is based on sample selection. Random...
Humans Datasets as Topic Female Support Vector Machine Breast Neoplasms Cluster Analysis Data Mining
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Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.

Artificial intelligence in medicine Aug 9, 2019
INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learnin...
Depression Decision Trees Models, Biological Schizophrenia Mental Disorders Data Mining Humans Psychiatry Alzheimer Disease Precision Medicine Artificial Intelligence Machine Learning
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Combining a gravitational search algorithm, particle swarm optimization, and fuzzy rules to improve the classification performance of a feed-forward neural network.

Computer methods and programs in biomedicine Aug 8, 2019
BACKGROUND AND OBJECTIVE: A feed-forward neural network (FNN) is a type of artificial neural network that has been widely used in medical diagnosis, data mining, stock market analysis, and other fields. Many studies have used FNN to develop medical d...
Lung Neoplasms Renal Insufficiency, Chronic Fuzzy Logic Data Mining Mesothelioma Mesothelioma, Malignant Machine Learning Algorithms Diagnostic Errors Humans Neural Networks, Computer
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Cross-registry neural domain adaptation to extract mutational test results from pathology reports.

Journal of biomedical informatics Aug 8, 2019
OBJECTIVE: We study the performance of machine learning (ML) methods, including neural networks (NNs), to extract mutational test results from pathology reports collected by cancer registries. Given the lack of hand-labeled datasets for mutational te...
Humans Registries Data Mining Neural Networks, Computer Machine Learning Neoplasms ErbB Receptors Computational Biology Deep Learning Carcinoma, Non-Small-Cell Lung Lung Neoplasms Mutation
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Hierarchical Hidden Markov models enable accurate and diverse detection of antimicrobial resistance sequences.

Communications biology Aug 6, 2019
The characterization of antimicrobial resistance genes from high-throughput sequencing data has become foundational in public health research and regulation. This requires mapping sequence reads to databases of known antimicrobial resistance genes to...
Databases, Genetic Metagenomics Machine Learning Data Mining Sequence Analysis, DNA Reproducibility of Results Drug Resistance, Microbial High-Throughput Nucleotide Sequencing Markov Chains
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Adaptive robust principal component analysis.

Neural networks : the official journal of the International Neural Network Society Aug 1, 2019
Robust Principal Component Analysis (RPCA) is a powerful tool in machine learning and data mining problems. However, in many real-world applications, RPCA is unable to well encode the intrinsic geometric structure of data, thereby failing to obtain t...
Machine Learning Algorithms Cluster Analysis Principal Component Analysis Data Mining
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Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.

Pharmacology & therapeutics Jul 30, 2019
A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into e...
Machine Learning Computer Simulation Animals Neoplasms Treatment Outcome Data Mining Humans
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Using distant supervision to augment manually annotated data for relation extraction.

PloS one Jul 30, 2019
Significant progress has been made in applying deep learning on natural language processing tasks recently. However, deep learning models typically require a large amount of annotated training data while often only small labeled datasets are availabl...
Data Mining Data Curation Models, Theoretical Natural Language Processing Humans Deep Learning
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