# Physionet ArticleInfo scraper (`getdataforme/physionet-articleinfo-scraper`) Actor The Physionet ArticleInfo Scraper efficiently extracts detailed data from Physionet articles, ideal for researchers and analysts. It retrieves titles, authors, and citations, ensuring high-quality, up-to-date information.... - **URL**: https://apify.com/getdataforme/physionet-articleinfo-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Physionet ArticleInfo Scraper ### Introduction The Physionet ArticleInfo Scraper is a powerful tool designed to extract detailed information from Physionet articles. This Actor is ideal for researchers, data analysts, and developers who need structured data from Physionet's extensive database of ECG signal records and annotations. ### Features - **Comprehensive Data Extraction**: Retrieves detailed article information including titles, descriptions, authors, and citations. - **High Data Quality**: Ensures accurate and up-to-date information by scraping directly from Physionet. - **Efficient Performance**: Optimized for fast data retrieval, handling multiple URLs simultaneously. - **User-Friendly Interface**: Easy to configure and run with minimal setup required. - **Flexible Output Formats**: Export data in JSON, CSV, or Excel formats to suit your needs. - **Open Access Compliance**: Extracts data that adheres to open access licensing, ensuring ethical use. ### Input Parameters | Parameter | Type | Required | Description | Example | |------------|--------|----------|------------------------------|----------------------------------------------| | startUrls | Array | Yes | URLs to start with. | ["https://physionet.org/content/but-pdb/1.0.0/"] | ### Example Usage #### Example Input JSON ```json { "startUrls": [ { "url": "https://physionet.org/content/but-pdb/1.0.0/" } ] } ```` #### Example Output JSON ```json [ { "url": "https://physionet.org/content/but-pdb/1.0.0/", "title": "Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB)", "description": "BUT PDB is an ECG signal database with marked peaks of P waves...", "version": ".", "publishedDate": "Jan. 19, 2021. Version:\n 1.0.0", "access": { "type": "Open Access", "license": "Creative Commons Attribution 4.0 International Public License", "licenseUrl": "/content/but-pdb/view-license/1.0.0/" }, "authors": [ { "name": "Lucie Mar\u0161\u00e1nov\u00e1", "affiliations": [ "Brno University of Technology" ], "profileUrl": "https://physionet.org/users/luciem" } ], "citation": { "text": "Mar\u0161\u00e1nov\u00e1, L., Nemcova, A., Smisek, R., Smital, L., & Vitek, M. (2021)...", "doi": "10.13026/hwvj-5b53", "bibtex": "@article{PhysioNet-but-pdb-1.0.0,...}" }, "abstract": "Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB)...", "background": "Accurate detection of P waves and subsequent cardiac pathological events...", "methods": "The ECGs were selected from three existing databases of ECG signal...", "dataDescription": { "text": "The database consists of 50 2-minute 2-lead ECG signals...", "pathologyTable": [ { "abbreviation": "A", "name": "Atrial premature beat", "count": 14, "signals": "4,5,9,16,17,18,26,28,35,38,39,40,41,43" } ] }, "usageNotes": "There are few publicly available databases of ECG signals...", "acknowledgements": "This work was funded by the United States Office of Naval Research...", "conflictsOfInterest": "The authors declare that there are no known conflicts of interest.", "references": [ "Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000)..." ], "parentProjects": [ { "name": "Long Term AF Database v1.0.0", "url": "https://physionet.org/content/ltafdb/1.0.0/" } ], "files": [ { "name": "01.dat", "size": "168.8 KB", "modified": "2020-11-14", "url": "https://physionet.org01.dat" } ], "totalSize": "7.0 MB", "doi": "10.13026/hwvj-5b53", "topics": [ "p wave", "ecg" ] } ] ``` ### Use Cases - **Academic Research**: Gather comprehensive ECG data for medical studies. - **Content Aggregation**: Compile ECG signal databases for educational purposes. - **Market Research**: Analyze trends in ECG signal databases. - **Competitive Intelligence**: Monitor updates in ECG signal data. - **Business Automation**: Automate data collection for healthcare analytics. ### Installation and Usage ``` 1. Search for "Physionet ArticleInfo scraper" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ``` ### Output Format The output is a JSON array containing objects with fields such as `url`, `title`, `description`, `version`, `publishedDate`, `access`, `authors`, `citation`, `abstract`, `background`, `methods`, `dataDescription`, `usageNotes`, `acknowledgements`, `conflictsOfInterest`, `references`, `parentProjects`, `files`, `totalSize`, `doi`, and `topics`. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## Actor input object example ```json { "startUrls": [ { "url": "https://physionet.org/content/but-pdb/1.0.0/" } ] } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://physionet.org/content/but-pdb/1.0.0/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/physionet-articleinfo-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [{ "url": "https://physionet.org/content/but-pdb/1.0.0/" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/physionet-articleinfo-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://physionet.org/content/but-pdb/1.0.0/" } ] }' | apify call getdataforme/physionet-articleinfo-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/physionet-articleinfo-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Physionet ArticleInfo scraper", "description": "The Physionet ArticleInfo Scraper efficiently extracts detailed data from Physionet articles, ideal for researchers and analysts. It retrieves titles, authors, and citations, ensuring high-quality, up-to-date information....", "version": "0.0", "x-build-id": "elbdVBrpSYBs3uqWE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~physionet-articleinfo-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-physionet-articleinfo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~physionet-articleinfo-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-physionet-articleinfo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~physionet-articleinfo-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-physionet-articleinfo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```