Taking clinical trials to the next level with NLP

“It is important to not discard clinical text in favor of screening or other structured methods for data collection,” the researchers noted. Researchers have developed natural language processing tools to pull data from clinical notes that will help address social drivers of health. LLMs are beneficial for businesses looking to automate processes that require human language. Because of their in-depth training and ability to mimic human behavior, LLM-powered CX systems can do more than simply respond to queries based on preset options.

What Is Natural Language Processing (NLP)?

• Implementing an automated testing and monitoring solution allows you to continuously validate your AI-powered CX channels, catching any deviations in behavior before they impact customer experience.
• In a practical sense, there are many use cases for NLP models in the customer service industry.
• But not every bot is built the same, and your success in using AI is based on your ability to build a bot that meets your users’ specific needs.
• LLMs are a type of AI model that are trained to understand, generate and manipulate human language.

NLP Logix offers predictive modeling and machine learning capabilities to customers across industries, including financial services, energy, healthcare, government and human resources among them. Conversational and generative AI-powered CX channels such as chatbots and virtual agents have the potential to transform the ways that companies interact with their customers. AI-based systems can provide 24/7 service, improve a contact center team’s productivity, reduce costs, simulate human behavior during customer interactions and more.

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Throughout the training process, LLMs learn to identify patterns in text, which allows a bot to generate engaging responses that simulate human activity. The study noted that this technology would work best as part of an overall social health measurement strategy. By educating yourself on each model, you can begin to identify the best model for your business’s unique needs.

NLP is a branch of AI that is used to help bots understand human intentions and meanings based on grammar, keywords and sentence structure. NLPs break human language down into its basic components and then use algorithms to analyze and pull out the key information that’s necessary to understand a customer’s intent. “The demand from payers, policy-makers, and advocates for information on patients’ social factors and needs is substantial and multiple approaches are requested to obtain this information,” they noted in their study. “In recent years, coding standards for recording social risks as structured data within EHRs using ICD-10 or LOINC codes have advanced substantially. Nevertheless, these structured data are very underutilized in practice.” For example, tools like Generative Pre-trained Transformer 3 (GPT-3), developed by OpenAI, use a neural network machine learning model that can not only code but also write articles and answer questions, frequently in a manner virtually indistinguishable from a human response. The tools are designed to be used as part of a larger SDOH strategy, and to especially help providers who don’t have the expertise or resources to use sophisticated AI technology.

For example, dependent on the training data used, an LLM may generate inaccurate information or create a bias, which can lead to reputational risks or damage your customer relationships. The start-up Xembly is using an automated, NLP-powered platform to handle many office jobs that often get lost in the shuffle. Its conversational AI agent, Xena, can listen to meetings, take notes, schedule meetings through Slack or email, remind people of action items, and even understand who is talking to whom when there is more than one speaker. Whereas LLM-powered CX channels excel at generating language from scratch, NLP models are better equipped for handling well-defined tasks such as text classification and data extraction.

Let’s explore the various strengths and use cases for two commonly used bot technologies—large language models (LLMs) and natural language processing (NLP)—and how each model is equipped to help you deliver quality customer interactions. Researchers in Indiana have created three NLP algorithms to scan clinical notes for data on housing challenges, financial instability, and employment status. Vest and his team developed three rule-based NLP algorithms and scanned notes from two different Indiana-based health systems, targeting keywords specific to three social factors. In a study recently published in JAMIA Open, researchers at the Regenstrief Institute and the Indiana University Fairbanks School of Public Health created basic algorithms to screen unstructured notes in the EHR for data on housing challenges, financial instability, and employment status.

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“We purposely designed a system that could run in the background, read all the notes and create tags or indicators that says this patient’s record contains data suggesting possible concern about a social indicator related to health,” he said in the press release. The technology aims to help healthcare providers address SDOH in care management and treatment plans for patients. However, when it comes to more diverse tasks that require a deeper understanding of context, NLP models lack the capacity to generate new content.

NLP Tech Can Help Providers Address Social Drivers of Health

W. David Freeman, MD, a neurologist at the Mayo Clinic in Florida said Mayo would focus on developing a suite of stroke detection algorithms, which would be taught by using the vast amount of de-identified clinical data Mayo Clinic has collected over the years. Alok Kulkarni is Co-Founder and CEO of Cyara, a customer experience (CX) leader trusted by leading brands around the world. Although Xena may never be able to clear out the refrigerator in your office building or ensure everyone actually signs a birthday card, the agent is likely a harbinger of bigger things to come in the NLP world. Smart companies are already considering how to utilize NLP and other AI tools to make their workplaces more efficient and profitable. And smart investors will pay attention to these tools and how they’re used as they continue to develop.

Because NLP models are focused on language rules, ambiguity can lead to misinterpretations. Founded in 1993, The Motley Fool is a financial services company dedicated to making the world smarter, happier, and richer. The Motley Fool reaches millions of people every month through our premium investing solutions, free guidance and market analysis on Fool.com, personal finance education, top-rated podcasts, and non-profit The Motley Fool Foundation. The Motley Fool reaches millions of people every month through our premium investing solutions, free guidance and market analysis on Fool.com, top-rated podcasts, and non-profit The Motley Fool Foundation. Vest said the study is one of the first to apply NLP tools to SDOH collection, and it points to the value of using a “relatively simplistic” tool to collect data from notes rather than more sophisticated AI tools that many health systems can’t use or afford. However, when LLMs lack proper governance and oversight, your business may be exposed to unnecessary risks.