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Retrieval is the process of getting information out of memory storage and back into conscious awareness. This ability is essential for daily tasks like brushing hair and teeth, driving to work, and performing job duties. Retrieval occurs in three ways: recall, recognition, and relearning.
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Microorganisms play a fundamental role in vaccine development, gene therapy, and therapeutic production. Their biological properties are harnessed to advance medicine and public health. Beyond immunization, microorganisms contribute to gut health, antibiotic synthesis, and genetic disease treatment.Live Attenuated and Inactivated VaccinesLive attenuated vaccines, such as the measles, mumps, and rubella (MMR) vaccine, utilize weakened forms of pathogens to closely resemble natural infections.
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ARtPM: Article Retrieval for Precision Medicine.

Lowell K Milliken1, Sirisha K Motomarry1, Anagha Kulkarni1

  • 1Department of Computer Science, San Francisco State University, 1600 Holloway Avenue, San Francisco 94132, USA.

Journal of Biomedical Informatics
|June 15, 2019
PubMed
Summary

A new system, Article Retrieval for Precision Medicine (ARtPM), aids evidence-based precision medicine by retrieving relevant articles. ARtPM shows promise but requires further development for early-rank precision.

Keywords:
Biomedical information retrievalBiomedical knowledge curationDocument retrievalLearning to rankPrecision medicineQuery expansion

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Area of Science:

  • Biomedical Informatics
  • Genomics
  • Pharmacogenomics

Background:

  • Synthesizing knowledge on genetic variability's impact on disease and drug response is crucial for precision medicine.
  • Challenges exist in identifying comprehensive and relevant articles from vast scientific literature.

Purpose of the Study:

  • To develop and evaluate an end-to-end article retrieval system, Article Retrieval for Precision Medicine (ARtPM), for precision medicine applications.
  • To compare ARtPM's performance against established search methods, including PubMed Best Match.

Main Methods:

  • ARtPM utilizes a multi-stage architecture for retrieving and ranking articles based on medical case summaries.
  • Performance evaluation involved statistical comparison against five baseline systems using metrics like P@10, R-prec, infNDCG, and Recall@1000.

Main Results:

  • ARtPM demonstrated statistically significant improvements over baselines in recall and overall effectiveness (R-prec, infNDCG, Recall@1000).
  • While ARtPM's recall-focused phase is effective, its precision-focused ranking needs enhancement for early-rank performance (P@10).

Conclusions:

  • The ARtPM system effectively supports evidence-based precision medicine by improving article retrieval.
  • Further research is needed to optimize early-rank precision in the ARtPM system.