AI Medical Compendium Topic:
Data Mining

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ToBio: Global Pathway Similarity Search Based on Topological and Biological Features.

IEEE/ACM transactions on computational biology and bioinformatics
Pathway similarity search plays a vital role in the post-genomics era. Unfortunately, pathway similarity search involves the graph isomorphism problem which is NP-complete. Therefore, efficient search algorithms are desirable. In this work, we propos...

SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.

Artificial intelligence in medicine
With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., dr...

Semantic biclustering for finding local, interpretable and predictive expression patterns.

BMC genomics
BACKGROUND: One of the major challenges in the analysis of gene expression data is to identify local patterns composed of genes showing coherent expression across subsets of experimental conditions. Such patterns may provide an understanding of under...

Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks.

International journal of neural systems
One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated m...

A new synonym-substitution method to enrich the human phenotype ontology.

BMC bioinformatics
BACKGROUND: Named entity recognition is critical for biomedical text mining, where it is not unusual to find entities labeled by a wide range of different terms. Nowadays, ontologies are one of the crucial enabling technologies in bioinformatics, pro...

An automatic approach for constructing a knowledge base of symptoms in Chinese.

Journal of biomedical semantics
BACKGROUND: While a large number of well-known knowledge bases (KBs) in life science have been published as Linked Open Data, there are few KBs in Chinese. However, KBs in Chinese are necessary when we want to automatically process and analyze electr...

Multiple kernels learning-based biological entity relationship extraction method.

Journal of biomedical semantics
BACKGROUND: Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the ...

Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

Journal of biomedical semantics
BACKGROUND: Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to dis...

Living systematic reviews: 2. Combining human and machine effort.

Journal of clinical epidemiology
New approaches to evidence synthesis, which use human effort and machine automation in mutually reinforcing ways, can enhance the feasibility and sustainability of living systematic reviews. Human effort is a scarce and valuable resource, required wh...

Design of an extensive information representation scheme for clinical narratives.

Journal of biomedical semantics
BACKGROUND: Knowledge representation frameworks are essential to the understanding of complex biomedical processes, and to the analysis of biomedical texts that describe them. Combined with natural language processing (NLP), they have the potential t...