AI Medical Compendium Topic:
Data Mining

Clear Filters Showing 941 to 950 of 1549 articles

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...

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

Journal of vascular surgery
OBJECTIVE: A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aim...

Using machine learning to model dose-response relationships.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Establishing the relationship between various doses of an exposure and a response variable is integral to many studies in health care. Linear parametric models, widely used for estimating dose-response relationships, h...

SWIFT-Review: a text-mining workbench for systematic review.

Systematic reviews
BACKGROUND: There is growing interest in using machine learning approaches to priority rank studies and reduce human burden in screening literature when conducting systematic reviews. In addition, identifying addressable questions during the problem ...

Representing higher-order dependencies in networks.

Science advances
To ensure the correctness of network analysis methods, the network (as the input) has to be a sufficiently accurate representation of the underlying data. However, when representing sequential data from complex systems, such as global shipping traffi...