AIMC Topic: Information Storage and Retrieval

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PreMedKB: an integrated precision medicine knowledgebase for interpreting relationships between diseases, genes, variants and drugs.

Nucleic acids research
One important aspect of precision medicine aims to deliver the right medicine to the right patient at the right dose at the right time based on the unique 'omics' features of each individual patient, thus maximizing drug efficacy and minimizing adver...

PLATYPUS: A Multiple-View Learning Predictive Framework for Cancer Drug Sensitivity Prediction.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Cancer is a complex collection of diseases that are to some degree unique to each patient. Precision oncology aims to identify the best drug treatment regime using molecular data on tumor samples. While omics-level data is becoming more widely availa...

Transfer learning for biomedical named entity recognition with neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/protei...

Deep neural networks and distant supervision for geographic location mention extraction.

Bioinformatics (Oxford, England)
MOTIVATION: Virus phylogeographers rely on DNA sequences of viruses and the locations of the infected hosts found in public sequence databases like GenBank for modeling virus spread. However, the locations in GenBank records are often only at the cou...

Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information.

Bioinformatics (Oxford, England)
MOTIVATION: Most gene prioritization methods model each disease or phenotype individually, but this fails to capture patterns common to several diseases or phenotypes. To overcome this limitation, we formulate the gene prioritization task as the fact...

pBRIT: gene prioritization by correlating functional and phenotypic annotations through integrative data fusion.

Bioinformatics (Oxford, England)
MOTIVATION: Computational gene prioritization can aid in disease gene identification. Here, we propose pBRIT (prioritization using Bayesian Ridge regression and Information Theoretic model), a novel adaptive and scalable prioritization tool, integrat...

Enhanced functionalities for annotating and indexing clinical text with the NCBO Annotator.

Bioinformatics (Oxford, England)
SUMMARY: Second use of clinical data commonly involves annotating biomedical text with terminologies and ontologies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally designed for biomedical dat...

SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Unlocking the data contained within both structured and unstructured components of electronic health records (EHRs) has the potential to provide a step change in data available for secondary research use, generation of actionable medical i...

Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning.

JAMA oncology
This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a deep learning–based signal generation pipeline to capture how patients describe cutaneous eruptions.

Automatic Processing of Anatomic Pathology Reports in the Italian Language to Enhance the Reuse of Clinical Data.

Studies in health technology and informatics
Medical reports often contain a lot of relevant information in the form of free text. To reuse these unstructured texts for biomedical research, it is important to extract structured data from them. In this work, we adapted a previously developed inf...