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Melax Tech Introduces Mercury NLP – AI Technology To Improve Healthcare Research

Artificial Intelligence (AI) , Machine Learning (ML), Natural Language Processing (NLP), Deep Learning (DL), AI Model, AI-powered Solutions, Digital Transformation, ML Model, Natural Language Understanding (NLU), AI News, Artificial Intelligence News
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Melax Tech, a provider of natural language processing (NLP) software, announced the launch of Mercury NLP, which provides clinical NLP pipelines for capturing relevant textual health data and facilitating quantitative analysis in the medical and pharmaceutical industries, among other fields. Mercury NLP provides easy and rapid access to text data from a variety of formats, and it can be run either in a cloud environment or on-premises.

Frank Manion, Ph.D., Vice President for Innovation at Melax Tech, stated, “We are confident Mercury NLP will foster important breakthroughs in medical research. NLP technology is a largely untapped tool, and we want to change this by showcasing the benefits that it can provide in healthcare and other biomedical domains, where as much as 80% of data is housed in unstructured text notes.”

A Mercury NLP software solution is half the cost per byte of its closest competitors. It can be customized for clients with specific data warehousing objectives since Mercury NLP has built-in features to suit all processing solutions.

With the new product, users will no longer need to manually extract data from unstructured medical texts. With Melax Tech’s Mercury NLP software, doctors and their staff can extract accurate, real-time text data around diagnoses, prescribed medications, tests, lab results, discharge plans, etc. Additionally, the technology can be used to improve public health by analyzing data on social determinants.

As part of their NLP suite, Melax Tech also offers COVID-19 symptom extractor software based on CLAMP, their flagship product. The company also offers a medical chart text extraction product called VITAL and a text annotation product called LANN.

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