Case Studies Fortune 500 Biotech Pioneer Uses Snorkel Flow for Chronic Disease Data Extraction

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	Fortune 500 Biotech Pioneer Uses Snorkel Flow for Chronic Disease Data Extraction

Fortune 500 Biotech Pioneer Uses Snorkel Flow for Chronic Disease Data Extraction

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Healthcare & Hospitals Life Sciences
Applicable Functions	Product Research & Development Quality Assurance
Services	Software Design & Engineering Services System Integration
Challenge	Building AI applications to extract entities requires high domain expertise and large amounts of labeled training data, which is expensive and time-consuming. The biotech company faced the challenge of processing a vast amount of clinical trial documents to extract critical chronic disease data. Traditional methods of manual labeling were not only slow but also costly, making it impractical for the scale required. The need for a more efficient and accurate solution was paramount to meet the demands of their research and development processes. Read More
About Customer	The customer is a Fortune 500 biotech pioneer known for its innovative approaches in the life sciences and healthcare sectors. This company is at the forefront of developing treatments and conducting extensive clinical trials to address chronic diseases. With a large-scale operation and a significant amount of data to process, the company required advanced technological solutions to maintain its competitive edge and continue its groundbreaking work. The biotech giant has a global presence and is committed to leveraging cutting-edge technology to enhance its research capabilities and operational efficiency. Read More
Solution	The biotech company implemented Snorkel Flow to address their data extraction challenges. Snorkel Flow allowed them to build a custom machine learning model with an impressive 99.1% accuracy. By adjusting the label schema and re-labeling programmatically, they were able to streamline the data extraction process significantly. This approach eliminated the need for extensive manual labeling, which was both time-consuming and costly. The use of Snorkel Flow enabled the company to process approximately 300,000 documents in minutes, a task that would have otherwise taken a substantial amount of time and resources. The solution not only improved accuracy but also drastically reduced the time required to adjust label schemas from one year to just one day. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Healthcare & Hospitals

Life Sciences

Applicable Functions

Product Research & Development

Quality Assurance

Services

Software Design & Engineering Services

System Integration

Challenge

Building AI applications to extract entities requires high domain expertise and large amounts of labeled training data, which is expensive and time-consuming. The biotech company faced the challenge of processing a vast amount of clinical trial documents to extract critical chronic disease data. Traditional methods of manual labeling were not only slow but also costly, making it impractical for the scale required. The need for a more efficient and accurate solution was paramount to meet the demands of their research and development processes.

About Customer

The customer is a Fortune 500 biotech pioneer known for its innovative approaches in the life sciences and healthcare sectors. This company is at the forefront of developing treatments and conducting extensive clinical trials to address chronic diseases. With a large-scale operation and a significant amount of data to process, the company required advanced technological solutions to maintain its competitive edge and continue its groundbreaking work. The biotech giant has a global presence and is committed to leveraging cutting-edge technology to enhance its research capabilities and operational efficiency.

Solution

The biotech company implemented Snorkel Flow to address their data extraction challenges. Snorkel Flow allowed them to build a custom machine learning model with an impressive 99.1% accuracy. By adjusting the label schema and re-labeling programmatically, they were able to streamline the data extraction process significantly. This approach eliminated the need for extensive manual labeling, which was both time-consuming and costly. The use of Snorkel Flow enabled the company to process approximately 300,000 documents in minutes, a task that would have otherwise taken a substantial amount of time and resources. The solution not only improved accuracy but also drastically reduced the time required to adjust label schemas from one year to just one day.

Impact #1	The biotech company was able to programmatically label around 300,000 documents in minutes, showcasing a significant improvement in processing speed.
Impact #2	The implementation of Snorkel Flow resulted in a custom model with 99.1% accuracy, ensuring high-quality data extraction.
Impact #3	The solution allowed for rapid adjustments to the label schema, reducing the time required from one year to just one day.

Impact #1

The biotech company was able to programmatically label around 300,000 documents in minutes, showcasing a significant improvement in processing speed.

Impact #2

The implementation of Snorkel Flow resulted in a custom model with 99.1% accuracy, ensuring high-quality data extraction.

Impact #3

The solution allowed for rapid adjustments to the label schema, reducing the time required from one year to just one day.

Benefit #1	$10M saved on labeling for extraction
Benefit #2	99.1% accuracy on complex ML pipeline
Benefit #3	1 day vs. 1 year to adjust label schema

Benefit #1

$10M saved on labeling for extraction

Benefit #2

99.1% accuracy on complex ML pipeline

Benefit #3

1 day vs. 1 year to adjust label schema

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Overview

Fortune 500 Biotech Pioneer Uses Snorkel Flow for Chronic Disease Data Extraction

Operational Impact

Quantitative Benefit