# Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python

arXiv: https://arxiv.org/abs/2106.07799 · HTML: https://mlsanity.com/paper/2106.07799/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 41 references that are in the map.
- First posted on arXiv 14 Jun 2021.

## Builds on (most cited first, 2 of 2)

- [ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing](https://mlsanity.com/paper/1902.07669/) (2019)
- [Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review](https://mlsanity.com/paper/1908.05780/) (2019)

## Built on by (most cited first, 30 of 40)

- [RaTEScore: A Metric for Radiology Report Generation](https://mlsanity.com/paper/2406.16845/) (2024)
- [Large Language Models to Identify Social Determinants of Health in Electronic Health Records](https://mlsanity.com/paper/2308.06354/) (2023)
- [NoteChat: A Dataset of Synthetic Doctor-Patient Conversations Conditioned on Clinical Notes](https://mlsanity.com/paper/2310.15959/) (2023)
- [Data Extraction Attacks in Retrieval-Augmented Generation via Backdoors](https://mlsanity.com/paper/2411.01705/) (2024)
- [Literature-Augmented Clinical Outcome Prediction](https://mlsanity.com/paper/2111.08374/) (2021)
- [UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?](https://mlsanity.com/paper/2306.16931/) (2023)
- [Effective Matching of Patients to Clinical Trials using Entity Extraction and Neural Re-ranking](https://mlsanity.com/paper/2307.00381/) (2023)
- [HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools](https://mlsanity.com/paper/2402.12372/) (2024)
- [Radiology Text Analysis System (RadText): Architecture and Evaluation](https://mlsanity.com/paper/2204.09599/) (2022)
- [Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy](https://mlsanity.com/paper/2303.13722/) (2023)
- [Possible or Definite? A Benchmark for Evaluating Diagnostic Uncertainty Preservation in Clinical Text](https://mlsanity.com/paper/2606.18471/) (2026)
- [calamanCy: A Tagalog Natural Language Processing Toolkit](https://mlsanity.com/paper/2311.07171/) (2023)
- [Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation](https://mlsanity.com/paper/2311.16588/) (2023)
- [Extracting periodontitis diagnosis in clinical notes with RoBERTa and regular expression](https://mlsanity.com/paper/2311.10809/) (2023)
- [MedSlice: Fine-Tuned Large Language Models for Secure Clinical Note Sectioning](https://mlsanity.com/paper/2501.14105/) (2025)
- [EMSDialog: Synthetic Multi-person Emergency Medical Service Dialogue Generation from Electronic Patient Care Reports via Multi-LLM Agents](https://mlsanity.com/paper/2604.07549/) (2026)
- [EHRKit: A Python Natural Language Processing Toolkit for Electronic Health Record Texts](https://mlsanity.com/paper/2204.06604/) (2022)
- [Assessing mortality prediction through different representation models based on concepts extracted from clinical notes](https://mlsanity.com/paper/2207.10872/) (2022)
- [Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods](https://mlsanity.com/paper/2209.00470/) (2022)
- [An Automatic SOAP Classification System Using Weakly Supervision And Transfer Learning](https://mlsanity.com/paper/2211.14539/) (2022)
- [Cross-institution text mining to uncover clinical associations: a case study relating social factors and code status in intensive care medicine](https://mlsanity.com/paper/2301.06570/) (2023)
- [Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning](https://mlsanity.com/paper/2401.17602/) (2024)
- [A Typology of Synthetic Datasets for Dialogue Processing in Clinical Contexts](https://mlsanity.com/paper/2505.03025/) (2025)
- [Bias Detection in Emergency Psychiatry: Linking Negative Language to Diagnostic Disparities](https://mlsanity.com/paper/2509.02651/) (2025)
- [MTDiag: A Multi-Turn Diagnostic Dataset Towards Clinically Meaningful LLM Evaluation](https://mlsanity.com/paper/2608.25085/) (2026)
- [Natural Language Processing Methods to Identify Oncology Patients at High Risk for Acute Care with Clinical Notes](https://mlsanity.com/paper/2209.13860/) (2022)
- [Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN](https://mlsanity.com/paper/2211.08742/) (2022)
- [Clinical BioBERT Hyperparameter Optimization using Genetic Algorithm](https://mlsanity.com/paper/2302.03822/) (2023)
- [Applying unsupervised keyphrase methods on concepts extracted from discharge sheets](https://mlsanity.com/paper/2303.08928/) (2023)
- [Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition](https://mlsanity.com/paper/2403.16158/) (2024)

## Abstract (arXiv)

Despite impressive success of machine learning algorithms in clinical natural language processing (cNLP), rule-based approaches still have a prominent role. In this paper, we introduce medspaCy, an extensible, open-source cNLP library based on spaCy framework that allows flexible integration of rule-based and machine learning-based algorithms adapted to clinical text. MedspaCy includes a variety of components that meet common cNLP needs such as context analysis and mapping to standard terminologies. By utilizing spaCy's clear and easy-to-use conventions, medspaCy enables development of custom pipelines that integrate easily with other spaCy-based modules. Our toolkit includes several core components and facilitates rapid development of pipelines for clinical text.