Data Extraction System from Radiology Reports | Almawave
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Data Extraction System from Radiology Reports

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Automatic and secure extraction of radiological data

The solution facilitates automatic extraction of information from radiology reports using Natural Language Processing (NLP) techniques. Additionally, through pseudonymization, it ensures advanced protection of healthcare data.

Automatic extraction of information

Data Anonymization

Replicability in multiple clinical settings

Solution insights

Our solution is designed to simplify and streamline the way you work while making your business more efficient and productive.

How it works

Highlights

Use case

How it works

A tool for optimizing report reading

The solution employs Named Entity Recognition (NER) to extract essential information from radiology reports, such as patient demographics, medical history, clinical observations from diagnostic tests, examination results, and clinician assessments. Using the Natural Language Studio (NL Studio) tool on our AIWave platform, the solution annotates pseudonymized reports, enabling rapid and automated identification of relevant data while safeguarding patient privacy.

Highlights

Clear interpretation
of data

Advanced tools for understanding and interpreting human language (NLP technologies).

Automatic classification

Methodologies for the identification and categorization of named entities (NER).

Data security

Anonymization and pseudonymization methods to ensure patient privacy.

Use case

Instantly extracted data

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The challenge

For a scientifically oriented healthcare institute, selecting Almawave technology means efficiently gathering individual patient data with speed, accuracy, and comprehensiveness, while fully respecting privacy. This enables the data to be readily utilized for clinical studies and research purposes.

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The solution

Our extensive expertise in text analytics and natural language processing technologies enables us to extract large volumes of patient clinical variables (appropriately pseudonymized) from reports and convert these values into structured data. This structured data can then be used to populate datasets for further processing.

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The result

With the clinical outcomes of patients, the Institute can rapidly develop a comprehensive and detailed knowledge base. This foundation allows for the calculation of indicators, performance of statistical analyses, testing of hypotheses, and training of AI models. These models can be used to evaluate the evolution of individual cases (in a completely anonymized manner) and to conduct research on larger groups.

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Anonymization and Pseudonymization of Health Data

Safeguard sensitive patient data by automatically replacing real names with pseudonyms, ensuring compliance with privacy regulations.

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Do you want to make a difference in your business? With our expertise, we will achieve great results together.