AI Medical Compendium Topic:
Data Mining

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HANN: A Hybrid Model for Liver Syndrome Classification by Feature Assortment Optimization.

Journal of medical systems
Early detection of any sort of disease is mandatory for effective medical treatment. Medical diagnosis relies heavily on Data Mining for automated disease classification and detection. It relies on data mining algorithms to examine medical data. Live...

Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20.

BMC genetics
BACKGROUND: Multiple layers of genetic and epigenetic variability are being simultaneously explored in an increasing number of health studies. We summarize here different approaches applied in the Data Mining and Machine Learning group at the GAW20 t...

A document level neural model integrated domain knowledge for chemical-induced disease relations.

BMC bioinformatics
BACKGROUND: The effective combination of texts and knowledge may improve performances of natural language processing tasks. For the recognition of chemical-induced disease (CID) relations which may span sentence boundaries in an article, although exi...

Identifying health information technology related safety event reports from patient safety event report databases.

Journal of biomedical informatics
OBJECTIVE: The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model featu...

Integrating Language Model and Reading Control Gate in BLSTM-CRF for Biomedical Named Entity Recognition.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical named entity recognition (Bio-NER) is an important preliminary step for many biomedical text mining tasks. The current mainstream methods for NER are based on the neural networks to avoid the complex hand-designed features derived from var...

Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.

AMA journal of ethics
A significant proportion of elderly and psychiatric patients do not have the capacity to make health care decisions. We suggest that machine learning technologies could be harnessed to integrate data mined from electronic health records (EHRs) and so...

Extracting Biomedical Events with Parallel Multi-Pooling Convolutional Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical event extraction is important for medical research and disease prevention, which has attracted much attention in recent years. Traditionally, most of the state-of-the-art systems have been based on shallow machine learning methods, which r...

Automated ontology generation framework powered by linked biomedical ontologies for disease-drug domain.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The exponential growth of the unstructured data available in biomedical literature, and Electronic Health Record (EHR), requires powerful novel technologies and architectures to unlock the information hidden in the unstructu...

Low-rank representation with adaptive graph regularization.

Neural networks : the official journal of the International Neural Network Society
Low-rank representation (LRR) has aroused much attention in the community of data mining. However, it has the following twoproblems which greatly limit its applications: (1) it cannot discover the intrinsic structure of data owing to the neglect of t...