The advent of GPT-4, an advanced large language model, has opened up a plethora of opportunities in various industries, including healthcare. As I predicted a few months ago when the hype started, it was only a matter of time before healthcare companies started integrating these sophisticated language models into their services. The first significant integration came when Microsoft joined forces with Nuance, marking the first large tech player to openly commit to utilizing ChatGPT in real-world healthcare applications.
In the short period since then, numerous other companies have followed suit, integrating GPT-4 into their operations. It is safe to assume that this trend will continue, with an exponential increase in the number of healthcare companies leveraging the capabilities of large language models (LLMs).
As you see on the below infographic, several weeks ago – when we collected the data for this analysis – we found 17 companies that are already using GPT in their businesses. We displayed a short summary of how they use the GPT model and also the country they come from.
I’m sure that during the time it took to prepare this article and infographic, even more companies have already begun adopting these advanced tools, and soon it will be impossible to keep count of them.
We are in living in a revolution right now
The magnitude of change various artificial intelligence algorithms will bring to healthcare (to the word) is nothing short of revolutionary. We are on the brink of a new era, and I fully believe that the significance of these new solutions compares to the changes the internet brought to the world. It’s huge.
We did our fair share of discussing this future potential, writing a ton about how to get friends with AI, how to be cautious about it, what we can expect from it, and we even launched an AI course for everyone wanting to learn the necessary basics for this AI-laced healthcare future.
Let’s see what we can learn from the examples of the early ‘ChatGPT In Healthcare’ birds!
- Diverse company selection
The range of healthcare companies incorporating GPT-4 into their services is quite diverse. In addition to prominent players like Ada Health, Microsoft, and Doximity, numerous smaller digital health companies have also taken advantage of the technology. This reflects the versatility of LLMs and their potential to benefit companies of all sizes within the healthcare sector.
- Health management and coaching in the frontline
At the moment, one of the primary use cases of GPT-4 in healthcare stems from health management and coaching. That’s not surprising, the advanced conversational capabilities of these models significantly outperform earlier chatbot iterations, and can also meaningfully enhance human conversations. With the ability to provide personalised guidance and support, GPT-4 powered solutions have quickly become an attractive option for healthcare companies.
- Medical scribe tools
GPT-4 is also being employed for tasks that can be automated, such as medical scribe tools. These tools use large language models to transcribe and summarize in-person and remote medical encounters, including patient-doctor interactions, diagnoses, and treatment plans.
The benefits of implementing LLMs in medical scribe applications are easy to grasp: they can save tons of time, and address a major cause of physician burnout: excessive amounts of administration.
- US Dominance
Unsurprisingly, a majority of the companies integrating GPT-4 into their services are based in the United States. OpenAI, the creator of ChatGPT, is an American company, and the language model performs best in English. Furthermore, potential regulatory and legal hurdles may be easier to navigate for US-based companies accessing the service through an API.
Future Outlook
As the integration of GPT-4 into healthcare services continues to gain momentum, it will be intriguing to observe which large players will adopt these solutions and how they will navigate the current lack of regulation. The absence of clear guidelines presents potential challenges, as well as opportunities for abuse.
It is reasonable to anticipate that privacy issues may arise as healthcare companies navigate this regulatory vacuum. While we do not wish to be alarmist, the chances of privacy misconduct incidents occurring are solid – hard to move within boundaries if you don’t know what they are after all. As the industry evolves and adapts to the capabilities of GPT-4, it will be crucial to establish appropriate guidelines for the safe, secure, and ethical use of these algorithms in healthcare asap.
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