PubMed
PubMed is a free database including primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. The United States National Library of Medicine (NLM) at the National Institutes of Health maintains the database as part of the Entrez system of information retrieval.[1]
Not to be confused with PubMed Central.Contact
From 1971 to 1997, online access to the MEDLINE database had been primarily through institutional facilities, such as university libraries.[2] PubMed, first released in January 1996, ushered in the era of private, free, home- and office-based MEDLINE searching.[3] The PubMed system was offered free to the public starting in June 1997.[2]
In addition to MEDLINE, PubMed provides access to:
Many PubMed records contain links to full text articles, some of which are freely available, often in PubMed Central[5] and local mirrors, such as Europe PubMed Central.[6]
Information about the journals indexed in MEDLINE, and available through PubMed, is found in the NLM Catalog.[7]
As of 23 May 2023, PubMed has more than 35 million citations and abstracts dating back to 1966, selectively to the year 1865, and very selectively to 1809. As of the same date, 24.6 million of PubMed's records are listed with their abstracts, and 26.8 million records have links to full-text versions (of which 10.9 million articles are available, full-text for free).[8] Over the last 10 years (ending 31 December 2019), an average of nearly one million new records were added each year.
In 2016, NLM changed the indexing system so that publishers are able to directly correct typos and errors in PubMed indexed articles.[9]
PubMed has been reported to include some articles published in predatory journals. MEDLINE and PubMed policies for the selection of journals for database inclusion are slightly different. Weaknesses in the criteria and procedures for indexing journals in PubMed Central may allow publications from predatory journals to leak into PubMed.[10] The National Library of Medicine had respond that individual journal articles can be included in PMC to support the public access policies of research funders and that rigorous policies about journals and publishers ensure integrity of NLM literature databases.[11]
Characteristics[edit]
Website design[edit]
A new PubMed interface was launched in October 2009 and encouraged the use of such quick, Google-like search formulations; they have also been described as 'telegram' searches.[12] By default the results are sorted by Most Recent, but this can be changed to Best Match, Publication Date, First Author, Last Author, Journal, or Title.[13]
The PubMed website design and domain was updated in January 2020 and became default on 15 May 2020, with the updated and new features.[14] There was a critical reaction from many researchers who frequently use the site.[15]
Data mining of PubMed[edit]
Alternative methods to mine the data in PubMed use programming environments such as Matlab, Python or R. In these cases, queries of PubMed are written as lines of code and passed to PubMed and the response is then processed directly in the programming environment. Code can be automated to systematically query with different keywords such as disease, year, organs, etc.
In addition to its traditional role as a biomedical database, PubMed has become common resource for training biomedical language models.[51] Recent advancements in this field include the development of models like PubMedGPT, a 2.7B parameter model trained on PubMed data by Stanford CRFM, and Microsoft's BiomedCLIP-PubMedBERT, which utilizes figure-caption pairs from PubMed Central for vision-language processing. These models demonstrate the significant potential of PubMed data in enhancing the capabilities of AI in medical research and healthcare applications. Such advancements underline the growing intersection between large-scale data mining and AI development in the biomedical field.
The data accessible by PubMed can be mirrored locally using an unofficial tool such as MEDOC.[52]
Millions of PubMed records augment various open data datasets about open access, like Unpaywall. Data analysis tools like Unpaywall Journals are used by libraries to assist with big deal cancellations: libraries can avoid subscriptions for materials already served by instant open access via open archives like PubMed Central.[53]