Physiotherapy Evidence QA Bilingual
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- cc-by-4.0
- Source / creator
- serhanayberkkilic/physiotherapy-evidence-qa
- Collection method
- Per the publisher, the corpus was expert-curated around evidence-based physiotherapy literature, with Turkish and English pairs aligned to support cross-lingual use. The dataset targets musculoskeletal rehabilitation, standardized outcome measures, and clinical research methodology topics. Specifics of source-document sampling and curation workflow are not fully documented on the dataset card.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
Source does not document detailed provenance of underlying evidence sources, annotator credentials, inter-annotator agreement, or QA validation procedures; buyers should validate empirically. Coverage is limited to Turkish and English, and to the physiotherapy/musculoskeletal domain — not a general medical QA corpus. Alignment quality between TR and EN pairs is asserted but not quantified. Not deduplicated against public medical QA benchmarks — leakage risk if used to train models later evaluated on MedQA-style suites.
Sample structure score: 100 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 140 of 140 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 140 of 140 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| question_tr | 0 / 10 | string | 0 / 10 |
| answer_tr | 0 / 10 | string | 0 / 10 |
| question_en | 0 / 10 | string | 0 / 10 |
| answer_en | 0 / 10 | string | 0 / 10 |
| disease_category_tr | 0 / 10 | string | 0 / 10 |
| disease_category_en | 0 / 10 | string | 0 / 10 |
| question_type_tr | 0 / 10 | string | 0 / 10 |
| question_type_en | 0 / 10 | string | 0 / 10 |
| difficulty_tr | 0 / 10 | string | 0 / 10 |
| difficulty_en | 0 / 10 | string | 0 / 10 |
| keywords_tr | 0 / 10 | string | 0 / 10 |
| keywords_en | 0 / 10 | string | 0 / 10 |
| source_file | 0 / 10 | string | 0 / 10 |
| source_page | 0 / 10 | number | 0 / 10 |
About this data
Expert-curated Turkish and English question-answer pairs covering evidence-based physiotherapy, musculoskeletal rehabilitation, outcome measures, and clinical research methodology.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py 71d5d4d0-3df1-4d5e-8c81-9189c71c9b87 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| question_tr | VARCHAR | Clinical or research question about physiotherapy in Turkish language |
| answer_tr | VARCHAR | Evidence-based answer to the Turkish question |
| question_en | VARCHAR | Clinical or research question about physiotherapy in English language |
| answer_en | VARCHAR | Evidence-based answer to the English question |
| disease_category_tr | VARCHAR | Musculoskeletal condition or disorder name in Turkish |
| disease_category_en | VARCHAR | Musculoskeletal condition or disorder name in English |
| question_type_tr | VARCHAR | Category of question (e.g., PT Treatment, Diagnosis, Outcome Measures) in Turkish |
| question_type_en | VARCHAR | Category of question (e.g., PT Treatment, Diagnosis, Outcome Measures) in English |
| difficulty_tr | VARCHAR | Question difficulty level (e.g., Kolay/Orta/Zor) in Turkish |
| difficulty_en | VARCHAR | Question difficulty level (e.g., Easy/Medium/Hard) in English |
| keywords_tr | VARCHAR | Comma-separated or JSON-array list of relevant medical/clinical terms in Turkish |
| keywords_en | VARCHAR | Comma-separated or JSON-array list of relevant medical/clinical terms in English |
| source_file | VARCHAR | PDF or document filename from which the Q&A pair was extracted |
| source_page | BIGINT | Page number (integer) in the source document where content originated |
Sample Data
Preview a sample of the data before downloading.
Public sample only. Sign in to retrieve the full dataset, including free datasets.
For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Physiotherapy Evidence QA Bili" })
// Found: 71d5d4d0-3df1-4d5e-8c81-9189c71c9b87
get_download_url({ dataset_id: "71d5d4d0-3df1-4d5e-8c81-9189c71c9b87" }) // free — sign in with MCP OAuth first# Free dataset — sign in or use your account API key: curl https://api.databazaar.io/datasets/71d5d4d0-3df1-4d5e-8c81-9189c71c9b87/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"