Limits...

OPENi RESTful Web Services

OPENi provides RESTful Web services. With this model you will need to keep track of which results you have retrieved and how to ask for the next or previous group of results.

Example:

Perform a search for the query term "heart murmur" and return the first 30 results.

The base URI is baseuri . In order to do the example query the base URI will need to provide 3 parameters.

The max delta of n-m allowed is 30. If n is equal to m you will get 1 result. If n is omitted the default number of results returned is 10. If m is not included the results start with the first record.

Click here for an explanation of all available parameters to filter your result.

Below is the proper URI query to retrieve the first 30 results for our query.

first example uri

to get the next thirty results from the URI that retrieved the first 30 results for "heart murmur" would be:

example 2 uri

Parameters m and n were incremented by 30 based upon the previous query json result having count=30.

The important fields in the JSON record for navigating the results are:

Here is the first JSON record of our initial query example.
{
    "min": 1,
    "max": 30,
    "count": 30,
    "total": 1356,
    "approximage": "false",
    "list": [ {
       "docSource": "",
       "title": "Heart energy signature spectrogram for cardiovascular diagnosis.",
       "pmid": "17480232",
       "pmcid": "1899182",
       "journal_title": "Biomedical engineering online",
       "journal_abbr": "Biomed Eng Online",
       "journal_date": {
             "day": "04",
             "month": "05",
             "year": "2007"
       },
       "fulltext_html_url": "http://www.biomedical-engineering-online.com/content/6/1/16",
       "pdf_url": "",
       "authors": "Kudriavtsev V, Polyshchuk V, Roy DL",
       "affiliate": "Biosignetics Corporation, Toronto, Canada. info@bsignetics.com",
       "pmc_url": "http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1899182",
       "pubMed_url": "http://www.ncbi.nlm.nih.gov/pubmed/17480232",
       "abstract": "A new method and application is proposed to characterize intensity and pitch of human heart sounds and murmurs. Using recorded heart sounds from the library of one of the authors, a visual map of heart sound energy was established. Both normal and abnormal heart sound recordings were studied. Representation is based on Wigner-Ville joint time-frequency transformations. The proposed methodology separates acoustic contributions of cardiac events simultaneously in pitch, time and energy. The resolution accuracy is superior to any other existing spectrogram method. The characteristic energy signature of the innocent heart murmur in a child with the S3 sound is presented. It allows clear detection of S1, S2 and S3 sounds, S2 split, systolic murmur, and intensity of these components. The original signal, heart sound power change with time, time-averaged frequency, energy density spectra and instantaneous variations of power and frequency/pitch with time, are presented. These data allow full quantitative characterization of heart sounds and murmurs. High accuracy in both time and pitch resolution is demonstrated. Resulting visual images have self-referencing quality, whereby individual features and their changes become immediately obvious.",
       "Outcome": [
             {
             "@score": "0.328",
             "#text": "The resolution accuracy is superior to any other existing spectrogram method."
             },
             {
             "@score": "0.212",
             "#text": "High accuracy in both time and pitch resolution is demonstrated."
             },
             {
             "@score": "0.235",
             "#text": "Resulting visual images have self-referencing quality, whereby individual features and their changes become immediately obvious."
             }
       ],
       "MeSH": {
             "minor": [
                   "Child",
                   "Computer Simulation",
                   "Energy Transfer",
                   "Humans",
                   "Models, Cardiovascular",
                   "Reproducibility of Results",
                   "Sensitivity and Specificity"
             ],
             "major": [
                   "Algorithms*",
                   "Diagnosis, Computer-Assisted/methods*",
                   "Heart/physiopathology*",
                   "Heart Murmurs/diagnosis*/physiopathology*",
                   "Phonocardiography/methods*",
                   "Sound Spectrography/methods*"
             ]
},
             "Problems": "transformation",
             "image": {
                   "id": "F4",
                   "caption": "(A-F). <b>Heart<\/b> Energy Signature (HES) Format and Innocent <b>Murmur<\/b> Details [see Additional file 2]. A) Instantaneous Peak Frequency (IPF) extracted from HES (F1: Eq. 17). B) Instantaneous Mean Frequency (IMF) extracted from HES (F1: Eq. 18). C) <b>Murmur<\/b> Signal Plot. D) <b>Murmur<\/b> HES. E) <b>Murmur<\/b> normalized square root of power, time duration is measured 118 ms, using 10% threshold value. F) <b>Murmur<\/b> IPF Plot. At time t = 0.263 s frequency is measured equal to 127.1 Hz.",
                   "mention": "In the majority of <b>heart<\/b> conditions a single <b>heart<\/b> beat is sufficient to define format. Let us assume that the <b>heart<\/b> beat is recorded during the time interval [τ, τ + T] with measurement instrument capable of capturing frequency range [f1, f2]. Thus, HES format includes (see also Figs. 3(A–E) and Figs. 4(A–B)):"
             },

            some links to more data

 

Further Parameters To Filter A Search

To Filter for Video: &vid=1

To Filter by Image Type use &it
Possible values to filter on are:

To Filter by RankBy use &favor
Possible values to filter on are:

To Filter by Subsets use &sub
Possible values to filter on are:

To Filter by Collection use &coll
Possible values to filter on are:

To Filter by Fields to search in use &fields
Possible values to filter on are:

To Filter by Specialties use &sp
Possible values to filter on are: