AMR Future Brief| Why Have Large Language Models (LLMs) Become Indispensable to the Healthcare Sector in 2024?

One distinctive feature of humans that separates them from animals is their ability to communicate with each other in a comprehensible, consistent, and syntactic language. Many evolutionary biologists have argued that this ability of humans has helped them become one of the most dominant species to have ever lived on the planet. In the past few years, researchers have been putting serious efforts to improve the quality of artificial intelligence and make it more ‘intelligent’. Taking a cue from evolutionary biology, AI researchers are focusing on improving the ability of the technology to understand, learn, and converse in languages in which humans communicate with each other.?

For this, researchers use large language models; these are foundational principles that are designed based on large amounts of data, thus making them capable of understanding, learning, and conversing in natural languages. These language models use machine learning algorithms, also called deep learning, to understand the characters, words, syntax, and sentence formation techniques. Furthermore, large language models (LLMs) are also trained using prompt tuning techniques to interpret questions and generate responses. Thus, large language models form the basis of innovative technologies such as generative AI.?

Understanding the evolution in the field of large language models?

The idea that a machine can be trained to understand human language can be traced back to the development of ‘ELIZA’, the world’s first chatbot. In 2013, a tool called word2vec was designed which made use of natural language processing techniques to capture the semantic meaning of words and sentences. In 2018, OpenAI, an artificial intelligence company, announced the launch of GPT i.e., Generative Pretrained Transformer for generating coherent text.?

In 2019 and 2020, subsequent versions of this pre-trained generative AI tool were released. Similarly, in 2021-2022, Google also jumped into the fray and launched a specialized language processing model called LaMDA for conversational applications. In the past few years, many other such tools have been developed that not only generate text but also use LLMs to create images from the description provided by the user. Along with this, these tools can offer various other functionalities including text classification, language modeling, dialogue systems, paraphrasing and rewriting, code generation and explanation, grammar correction, etc.?

Capitalizing on the opportunities offered by large language models in the healthcare sector?

Apart from simple text-to-image generation or vice versa, LLMs have widespread applicability in different sectors. In the healthcare sector, LLMs and AI-based tools are increasingly used to simplify the administrative procedures in hospitals and improve the healthcare outcomes of the patients. For example, LLMs have helped developers in building virtual medical assistants that respond to patient queries in real-time and offer general health information. Along with this, these assistants are also taught to provide medication reminders to the patients and aid doctors in communicating with their staff efficiently. Thus, large language models help in expanding the scope of telemedicine .?

Apart from this, software developers also use LLMs to create applications that can generate summaries of patient’s notes and medical records efficiently. Using such applications, doctors and healthcare practitioners can quickly extract information regarding a patient’s health and medical conditions and prescribe a treatment plan accordingly. Recently, in June 2024, Cognizant, a leading information technology company, announced the launch of healthcare large language model (LLM) solutions, specifically designed to improve the quality of healthcare administrative processes. Cognizant, in order to provide these solutions seamlessly, has partnered with Google Cloud's generative AI (genAI) technology which has helped the company to offer a wide range of services to medical institutions including marketing operations, provider management and contracting, call center operations, etc.?

Moreover, a recent study by a reputable medical institute found that large language models can analyze patient medical records to predict the likelihood of adverse events. Also, it has the capabilities to support monitoring and surveillance during drug delivery processes using the data captured from patient’s history and behavioral patterns.?

The final word??

In summary, though large language models have been used for a long time, the advent of artificial intelligence has increased their utility and popularity. These models have evolved massively in the past few years and are now used in different end-use industries such as the healthcare sector. From developing virtual medical assistants to detecting adverse events, LLMs have become indispensable to medical institutions in recent times.??

For more analysis on the applications and advancements in large language processing technology,?reach out to our analysts today!??

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? **?????????????? ????????????: Akhilesh Prabhugaonkar ?

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