Automated Indexing for Publication Types and Study Designs
出版物类型和研究设计的自动索引
基本信息
- 批准号:10715907
- 负责人:
- 金额:$ 32.17万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-08-02 至 2026-07-31
- 项目状态:未结题
- 来源:
- 关键词:Animal ModelAutomated IndexingBibliographic DatabasesDataDatabasesExplosionGuidelinesHealthHumanInfrastructureInterventionJournalsLiteratureManualsManuscriptsMedicalMethodsModelingPerformancePharmacologic SubstancePrintingPubMedPublicationsPublishingResearch DesignResearch PersonnelRetrievalStudentsTextUnited States National Library of Medicineeffectiveness studyhuman diseasehuman modelimprovedindexingmachine learning methodmachine learning modelneuralnovel therapeuticspreclinical studyprototypesystematic reviewtoolvector
项目摘要
Project Summary/Abstract
Retrieving biomedical articles from bibliographic databases requires accurate, detailed indexing of the topics
that are discussed as well as their publication types and study designs. It is difficult for indexers to keep up with
manual assignments in view of the explosion of published literature. Although NLM has recently employed
automatic machine learning methods to index articles according to the major topics discussed, there is still no
automatic means of indexing each article across all publication types and study designs. We have recently
created a working prototype tool, Multi-Tagger, which has assigned probabilistic predictive scores for all
PubMed articles for 50 different publication types and study designs (collectively, PTs). We now propose to
develop Multi-Tagger 2.0, to handle a wider variety of study designs, articles, users and use cases, and to
ensure that the data are disseminated in a form that is appropriate to each different type of user. Specifically,
we aim to:
Aim 1. Optimize methods for assigning Publication Types and study designs to both PubMed and non-
PubMed biomedical articles, preprints and manuscripts.
Aim 2. Evaluate PTs in detail, taking into account model performance, use cases and users.
Aim 3. Optimize dissemination of PT predictive scores by query interface and API.
Aim 4. Explore how to integrate Multi-Tagger with other tools for automating evidence synthesis.
The proposed studies will greatly enhance retrieval of relevant articles and preprints across multiple
databases, and will be useful for a wide range of biomedical end-users (clinicians, researchers, students and
journal editors) as well as user groups including systematic review groups, bibliographic database managers,
those studying preclinical animal models of human disease, and pharmaceutical companies developing new
drug treatments. Improving the infrastructure of the biomedical literature will thus indirectly impact on human
health.
项目总结/文摘
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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NEIL R SMALHEISER的其他文献
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{{ truncateString('NEIL R SMALHEISER', 18)}}的其他基金
RNAi-Mediated Gene Suppression in Adult Mammalian CNS
RNAi介导的成年哺乳动物中枢神经系统基因抑制
- 批准号:
6668489 - 财政年份:2002
- 资助金额:
$ 32.17万 - 项目类别:
RNAi-Mediated Gene Suppression in Adult Mammalian CNS
RNAi介导的成年哺乳动物中枢神经系统基因抑制
- 批准号:
6531730 - 财政年份:2002
- 资助金额:
$ 32.17万 - 项目类别:
Arrowsmith Data Mining Techniques in Neuro-Informatics
神经信息学中的 Arrowsmith 数据挖掘技术
- 批准号:
6333330 - 财政年份:2001
- 资助金额:
$ 32.17万 - 项目类别:
Arrowsmith Data Mining Techniques in Neuro-Informatics
神经信息学中的 Arrowsmith 数据挖掘技术
- 批准号:
6608110 - 财政年份:2001
- 资助金额:
$ 32.17万 - 项目类别:
相似海外基金
AUTOMATED INDEXING & NATURAL LANGUAGE RETRIEVAL OF RELATED ABSTRACTS
自动索引
- 批准号:
3874090 - 财政年份:
- 资助金额:
$ 32.17万 - 项目类别:














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