Announcing the New PubMed
becker.wustl.edu
becker.wustl.edu
1) The timeline graph is very cool. However I thought clicking "download csv" would give me a CSV of all the search results, which I was very excited for! I was sad to see it only downloaded a CSV detailing the number of results per year, not the results themselves.
2) Search history (found on the "advanced" search page) is something I am usually against, but on a site like PubMed, it's very nice to have. Great job implementing that in a clear and usable way. I recommend linking to it from somewhere on the basic search page... something like "View your search history" which will also help them discover the advanced page once they land on it.
I've worked with Google Scholar (:o) [1], Semantic Scholar (Allen Institute for AI) [2], Meta (Chan Zuckerberg Institute) [3], Zotero, Mendeley and a number of other tools for indexing and extracting metadata and graph relations from https://schema.org/ScholarlyArticle and MedicalScholarlyArticles . Without RDFa (or Microdata, or JSON-LD) in PDF, there's a lot of parsing that has to go down in order to get a graph from the citations in the article. Each service adds value to this graph of resources. Pushing forward on publishing linked research that's reproducible (#LinkedResearch, #LinkedReproducibility) is a worthwhile investment in meta-research that we have barely yet addressed:
> http://Schema.org/NewsArticle .citation: https://schema.org/citation ... Wouldn't it be great if NewsArticles linked to the ScholarlyArticle and/or Notebook CreativeWorks that they're .about (with reified relations)?
> A practical use case: Alice wants to publish a ScholarlyArticle [1] (in HTML with structured data, as a PDF) predicated upon Datasets [2] (as CSV, CSVW JSONLD, XLSX (DataDownload)) with static HTML (and no special HTTP headers). 1 https://schema.org/ScholarlyArticle 2 https://schema.org/Dataset*
> B wants to build a meta analysis: to collect a # of ScholarlyArticles and Dataset DataDownloads; review study controls and data; merge, join, & concatenate Datasets if appropriate, and inductively or deductively infer a conclusion and suggestions for further studies of variance*
The Linked Open Data Cloud shows the edges, the relations, the structured data links between very many (life sciences) datasets: https://lod-cloud.net/ . https://5stardata.info/en/ lists TimBL's suggested 5-start deployment schema for Open Data; which culuminates in publishing linked open data in non-proprietary formats that uses URIs to describe and link to things.
Could any of these [1][2][3][4][5] services cross-link the described resources, given a common URI identifier such as https://schema.org/identifier and/or https://schema.org/url ? ORCID is a service for generating stable identifiers for researchers and publishers who have names in common but different emails. W3C DID solves for this need in a different way.
When I check an article result page with the OpenLink OSDS extension (or any of a number of other tools for extracting structured data from HTML pages (and documents!) https://github.com/CodeForAntarctica/codeforantarctica.githu... ), there could be quite a bit more data there for search engines, browser extensions, and meta-research tools.
Is this something like ElasticSearch on the backend? It is possible to store JSON-LD documents in the search index. I threw together elasticsearchjsonld to "Generate JSON-LD @contexts from ElasticSearch JSON Mappings" for the OpenFDA FAERS data a few year ago. That's not GraphQL or SPARQL, but it's something and it's Linked Data.
re: "Canada's Decision To Make Public More Clinical Trial Data Puts Pressure On FDA" https://news.ycombinator.com/item?id=21232183
> We really could get more out of this data through international collaboration and through linked data (e.g. URIs for columns). See: "Open, and Linked, FDA data" https://github.com/FDA/openfda/issues/5#issuecomment-5392966... and "ENH: Adverse Event Count / 'Use' Count Heatmap" https://github.com/FDA/openfda/issues/49 . With sales/usage counts, we'd have a denominator with which we could calculate relative hazard.
W3C Web Annotations handle threaded comments and highlights; reviewing the reviewers is left as an exercise for the reader. Does Zotero still make it easy to save the bibliographic metadata for one or more ScholarlyArticles from PubMed to a collection in the cloud (and add metadata/annotations)?
Sorry to toot my own horn here. Great job on this. This opens up many new opportunities for research.
[1] https://scholar.google.com
ftp://ftp.ncbi.nlm.nih.gov/pubmed/
We had someone do a project with it. downloaded the dataset and used it and create a tool to do some searches that we found useful to find colaborators: (last author, working on a specific gene, paper counts, most recent).
Searching by Mesh Terms across species, and search with orthologs.
The dataset sometimes has a hard time disambiguating names (I think the european dataset assigns Ids to names)
is this effort limited to frontend / user experience or is pubmed changing on the backend side too ? (storage, analytics, etc)
The updated PubMed uses the Django Web framework on the front-end, making use of the latest web technologies and standards.
https://www.nlm.nih.gov/pubs/techbull/ma19/ma19_pubmed_updat...
lack of RSS feeds
specifically for the Trending articles.
ftp://ftp.ncbi.nlm.nih.gov/pubmed/updatefiles/
eg https://www.ncbi.nlm.nih.gov/pubmed/?term=30630823,30615641,...
Of course, reading through abstracts and papers requires a critical eye into the statistics, methodology, and funding. The Cochrane Reviews are similarly awesome.
I'm sure it can't be like that for all doctors, but it's been my (unfortunately vast and varied) experience.
Crucially I don’t think there’s a strong feedback loop for specialists. I was frustrated with my urologist. I just got a 2nd (and 3rd) opinion. But the information of “what you were doing hasn’t been working for me” didn’t make it back to my doctors. In part because it takes months to schedule an appointment. They also probably assume if they don’t see me, it just got better. This is partially because medicine is hard and there’s so much subjectivity in patient experiences. Crucially these specialists are in high demand, so they will find work, even if they really are just marginally effective.
Maybe there’s more “feedback” than I see, but That’s just my 2 cents from the patient perspective.
Should a patient come in with a preference for a treatment they read about on PubMed (which has never occurred in my practice) then I would likely accommodate their preference unless I thought it would put them at serious harm. A patient knowing more than I do about a particular disease happens more than you’d expect, especially if they have a rare chronic disorder. This does not diminish my ego or confidence in my knowledge base.
A friend of my family met 15 different doctors for a period lasting years because of agonizing headaches, they all sent her home thinking it was nothing unusual. She died of a brain tumor the size of a tennis ball. We often think about what would've happened if one of those 15 doctors would've shown some humility.
To be clear, I work in tech, we have more than our fair share of big egos too. I don't think this is anything particular about doctors.
I understand that 99% of patients are clueless and that most providing information are likely misinformed by whatever they read on google, but every so often you meet a patient that actually knows more than you about their problems. The experience for this rare patient is almost always very poor.
Seriously, PubMed is one of my favorite websites for its simplicity, speed and incredible usability. It has a querying system for hundreds of thousands of articles that makes sense, it saves these queries and allows you to edit them. It allows you to save articles to lists and makes them portable.
While it may be easy to just think of this as just another clever website redesign, I can tell you from personal experience that these increases in usability have a non-zero impact on research productivity. And since it’s PubMed, there’s a lot of important research at stake.
The new pubmed, much like the old pubmed, is speedy! Pages are ~800kb on first visit, subsequent pages visits avg 30kb transferred data in my very unscientific tests.
Congratulations on making a great resource greater :)
One thing I'm missing is a recommendation service of articles that might be relevant for me. I used to read a lot of Machine Learning/Math papers on arXiv and I have found arXiv-sanity [0] to be extremely useful, maybe something similar would be great as a part of PubMed functionality - being able to keep track of research which is relevant to the papers I've added to my favorites.
Also, I'm slightly confused by the sort order in the search. I found four options for sorting the items while searching:
* Default order
* Pub Date
* Journal
* PMC Live Date
IIUC "Default order" is not "sort by the number of citations/citation index", but that's what I typically want when I'm trying to figure out what are the most important/influential research in the field.
I also wish they got a shorter url.
Incredibly great work!