AI Medical Compendium Topic:
Data Mining

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Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction.

Journal of biomedical semantics
BACKGROUND: Clinical Natural Language Processing (NLP) systems require a semantic schema comprised of domain-specific concepts, their lexical variants, and associated modifiers to accurately extract information from clinical texts. An NLP system leve...

Large scale biomedical texts classification: a kNN and an ESA-based approaches.

Journal of biomedical semantics
BACKGROUND: With the large and increasing volume of textual data, automated methods for identifying significant topics to classify textual documents have received a growing interest. While many efforts have been made in this direction, it still remai...

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

Database : the journal of biological databases and curation
Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources...

Ensemble Feature Learning of Genomic Data Using Support Vector Machine.

PloS one
The identification of a subset of genes having the ability to capture the necessary information to distinguish classes of patients is crucial in bioinformatics applications. Ensemble and bagging methods have been shown to work effectively in the proc...

Improve Biomedical Information Retrieval Using Modified Learning to Rank Methods.

IEEE/ACM transactions on computational biology and bioinformatics
In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the...

DermO; an ontology for the description of dermatologic disease.

Journal of biomedical semantics
BACKGROUND: There have been repeated initiatives to produce standard nosologies and terminologies for cutaneous disease, some dedicated to the domain and some part of bigger terminologies such as ICD-10. Recently, formally structured terminologies, o...

TaggerOne: joint named entity recognition and normalization with semi-Markov Models.

Bioinformatics (Oxford, England)
MOTIVATION: Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine le...

Overlap in drug-disease associations between clinical practice guidelines and drug structured product label indications.

Journal of biomedical semantics
BACKGROUND: Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug structured product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medi...

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction.

Artificial intelligence in medicine
BACKGROUND AND AIMS: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, wit...

An ensemble method for extracting adverse drug events from social media.

Artificial intelligence in medicine
OBJECTIVE: Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them correctly and in a timely manner. With the development of Web 2.0, social media has become a large dat...