The Global Unique Device Identification Database (GUDID) contains key device identification information submitted to the FDA about medical devices that have Unique Device Identifiers (UDI).

Clinical Table Search Service (formerly "lforms-service") is a web service which software programs can use for querying clinical data tables. The API for each table is designed to work with our form field autocompletion package, but can be used by other programs as well. The tables may also be accessed through FHIR APIs. The FAQ page (https://clinicaltables.nlm.nih.gov/faq.html) has further details on terms of service, etc

***The Computational Photography Project for Pill Identification (C3PI) was discontinued in 2018. No new images will be added to the collection. Identifiers for pills will not be updated.***

The Computational Photography Project for Pill Identification (C3PI) created the RxIMAGE database of freely available high-quality digital images of prescription pills and associated data for use in conducting computer vision research in text- and image-based search and retrieval. Photographs of pills for the RxIMAGE database were taken under laboratory lighting conditions, from a camera directly above the front and the back faces of the pill, at high resolution, and using specialized digital macro-photography techniques. Image segmentation algorithms were then applied to create the JPEG images in the database.

Historical information about the project is available in the NLM archive at https://wayback.archive-it.org/7867/20190423182937/https:/lhncbc.nlm.nih.gov/project/c3pi-computational-photography-project-pill-identification.

The 17,000 NHANES images are available in the following formats:

jpg - full spatial resolution and 8-bit grayscale
jpgahe – jpg with adaptive histogram equalization (AHE)
jpgaheus - jpg with adaptive histogram equalization (AHE) followed by unsharp masking
tif8 - full spatial resolution and 8-bit grayscale resolution in TIFF format
tif8roi - A small subset of the cervical spine images is available at full spatial resolution and 8-bit, cropped to regions of interest containing the spine area
fullres - The 17,000 NHANES II images at full spatial and full 12-bit grayscale resolution, in raw "nh2" format, uncompressed
marks - Vertebra coordinate values for a subset of about 600 of the images is available in ASCII text format

Information about the Second National Health and Nutrition Examination Survey (NHANES II)

The National Health and Nutrition Examination Surveys

The National Health and Nutrition Examination Surveys (NHANES), conducted by the National Center for Health Statistics, Centers for Disease Control (NCHS/CDC), were designed to assess the health and nutritional status of adults and children in the United States through interviews and direct physical examinations.

These images are the digitized versions of the 17,000 x-ray films collected during the Second National Health and Nutrition Examination Survey (NHANES II) conducted by the NCHS during the years 1976-1980. In NHANES II 20,322 individuals were both interviewed and examined. For examined persons aged 25 through 74, two x-rays were made, with the exceptions that no x-rays were taken of pregnant women and no lumbar x-rays were taken on women under 50 years of age. X-rays of the cervical and lumbar spines were taken to provide evidence of osteoarthitis and degenerative disc disease.

The films were subsequently digitized at a horizontal and vertical sampling rate of 146 dpi using Lumisys laser scanning equipment.

The NHANES radiographs were scanned by Dr. Bernie Huang at the University of California at Los Angeles and the University of California at San Francisco. Dr. Huang’s group used a Lumysis 100 with a 175 micron spot to scan the first 6000 radiographs. The remaining radiographs were scanned on the Lumysis 150 again with a 175 micron spot size.

NOTE: This dataset is no-longer updated with new content.

I-MAGIC is an interactive tool to demonstrate how the SNOMED CT to ICD-10-CM map (https://www.nlm.nih.gov/research/umls/mapping_projects/snomedct_to_icd10cm.html) can be used to generate ICD-10-CM codes from clinical problems coded in SNOMED CT. It simulates a problem list entry interface in which the user searches for problem terms which are mapped to SNOMED CT codes in the back end. The SNOMED CT codes are then used to derive ICD-10-CM codes using the Map.

MAGPIE is an interactive tool to help users (e.g., professional coders, researchers, clinicians) find SNOMED CT and ICD-10-PCS codes for medical procedures and interventions. MAGPIE is an NLM research tool (it has not been tested in a production environment), and is developed primarily for the 2018 version of ICD-10-PCS. MAGPIE combines lexical and map-assisted searching strategies to look for SNOMED CT, ICD-9-CM, and ICD-10-PCS codes sequentially.

A system for producing indexing recommendations to assist in the indexing process at NLM. Currently provides indexing recommendations to more than 100 journals based on the NLM Medical Subject Headings (MeSH) vocabulary.

MTI is the main product of the Indexing Initiative project and has been providing indexing recommendations based on the Medical Subject Headings (MeSH®) vocabulary since 2002. In 2011, NLM expanded MTI's role by designating it as the first-line indexer (MTIFL) for a few journals; today the MTIFL workflow includes over 350 journals and continues to increase. The close collaboration of the NLM Index Section, Lister Hill National Center for Biomedical Communications, and Office of Computer & Communications Systems continues to expand and refine the ability of MTI to provide assistance to the indexers.

The MEDLINE/PubMed Baseline Repository (MBR) provides access to each MEDLINE/PubMed Baseline snapshot starting with the 2002 MEDLINE Baseline. Each baseline contains a snapshot of MEDLINE citations in the state they were at a given moment in time without the MeSH vocabulary updates and other revisions that occur during the year. The baseline snapshot is created at the beginning of each new MeSH Indexing Year. The records included in the MEDLINE/PubMed Baseline databases represent a static view of the data at the time each baseline database was created.

*A file containing all Min/Max Baseline Reports for 2005-2023 in their original format is available in the Attachments section below. A second file includes a separate set of reports, made available from 2002-2017, that did not include OLDMEDLINE records.*

MEDLINE/PubMed annual statistical reports are based upon the data elements in the baseline versions of MEDLINE®/PubMed are available. For each year covered the reports include: total citations containing each element; total occurrences of each element; minimum/average/maximum occurrences of each element in a record; minimum/average/maximum length of a single element occurrence; average record size; and other statistical data describing the content and size of the elements.

*A file containing all Misc Baseline Reports for 2018-2023 in their original format is available in the Attachments section below.*

MEDLINE/PubMed annual statistical reports are based upon the data elements in the baseline versions of MEDLINE®/PubMed are available. For each year covered the reports include: total citations containing each element; total occurrences of each element; minimum/average/maximum occurrences of each element in a record; minimum/average/maximum length of a single element occurrence; average record size; and other statistical data describing the content and size of the elements.