onconlp


Nameonconlp JSON
Version 0.1.0 PyPI version JSON
download
home_pagehttps://github.com/onconlp/onconlp
SummaryNatural Language Processing Toolkit for Oncology
upload_time2025-08-06 08:32:32
maintainerNone
docs_urlNone
authorOncoNLP Team
requires_python>=3.8
licenseNone
keywords oncology nlp medical text processing cancer research
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # OncoNLP

A comprehensive natural language processing toolkit for oncology and cancer research.

## Project Overview

OncoNLP is an advanced NLP framework specifically designed for processing and analyzing oncological texts, medical reports, and cancer-related documentation. It provides specialized tools for extracting meaningful insights from clinical narratives and research literature.

> ⚠️ **Development Notice**: This toolkit is currently in active development. While core functionality is being implemented, some features may be experimental or subject to change.

## Key Features

- Medical text preprocessing and normalization
- Cancer-specific information extraction
- Clinical report analysis and structuring
- Oncological knowledge graph construction
- Treatment outcome prediction
- Biomarker identification from text

## Technology Stack

- Python 3.8+
- Advanced NLP libraries (spaCy, NLTK, transformers)
- Medical text processing frameworks
- Machine learning models for healthcare
- Deep learning architectures for text analysis

## Installation

```bash
pip install onconlp
```

## Quick Start

```python
import onconlp

processor = onconlp.OncologyProcessor()
result = processor.analyze("Patient diagnosed with stage II lung adenocarcinoma...")
print(result.cancer_type, result.staging, result.biomarkers)
```

## Development Status

🚧 **Currently Under Development** - Version 0.1.0

**Note:** This project is actively being developed. Features and APIs may change as we continue to improve the toolkit. We welcome feedback and contributions from the community.

---
© 2024 OncoNLP Development Team

            

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