NLP and Language Models in Healthcare and the Life Sciences

Dia Trambitas-Miron and David Talby on what makes NLP in Health/Pharma/Biotech challenging and unique.

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This week’s guests are Dia Trambitas-Miron (Head of Product) and David Talby (CTO) of John Snow Labs, the startup behind the popular open source project, Spark NLP. The company also has a suite of products including an NLP platform targeted specifically for the healthcare, pharmaceutical, and biotech sectors. In this episode we discuss key NLP use cases in the healthcare sector, and what makes NLP in Health/Pharma/Biotech challenging and unique. We also look at broader trends in NLP and machine learning and discuss how those trends impact applications in healthcare.

If you’re interested in NLP and Language Models, make sure you attend the upcoming FREE Virtual Conference: 2022 Healthcare NLP Summit.

Dia Trambitas-Miron:

Recent deep learning and machine learning models have topped human performance in different tasks. But they are not 100% accurate. This is why we want to keep a human in the loop. We offer tools for clinicians and for health experts to quickly analyze text, but we also give them evidence from where this data was extracted, so that they can judge at the end if the data is correct or not. At the end of the day, they are the ones taking the responsibility for the decision or the clinical decision taken.

David Talby:

There are two things you need to do on your own, if you want to do this. One is just the algorithms, the neural architecture themselves, because deep learning models are just different for healthcare. The other thing you absolutely need is the data. We have a sizable team of clinicians who do this, you need people who are specialists.

Highlights in the video version:

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[Image: Medical Records in Hospital from Storyblocks.]