How we helped the Spanish Agency for Medicines and Health Products in building a Machine Learning model for extracting insights from their medical notes database for research purposes.

Spanish Agency for Medicines and Health Products

AEMPS has more than 20 million of anonymized medical records ready for research purposes, but the data is unstructured, then useless for research.


Generate training data to build a Named-Entity Recognition machine learning model to extract medical topics like clinical findings, medicines and dosages to help researchers.


A machine learning model that helps researchers to find information in the 20 million of medical records.

Revolutionize Medical Research with AEMPS: M47 Labs' Named-Entity Recognition Model Extracts Insights from 20 Million Records

AEMPS had over 20 million anonymized medical records available for research purposes. However, the data was unstructured and unusable for research, which makes it challenging to extract useful information. AEMPS needed a solution to make this data useful for research purposes.

M47's AI Platform has helped AEMPS to overcome the challenge of unstructured data and improve their medical research. The NER model has made it easier for researchers to find the information they need to conduct their studies, leading to more accurate and efficient research. This model can extract medical topics such as clinical findings, medicines, and dosages to help researchers find the information they need within the vast amounts of data.

The success of this project demonstrates the power of Machine Learning in improving data management and analysis for research purposes. Let us help you streamline your research and gain valuable insights from AEMPS' medical records.