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Artificial intelligence (AI) helped clinicians to accelerate the design of diabetes prevention software, a new study finds.
, the study examined the capabilities of generative AI, or GenAI, which predicts likely options for the next word in any sentence based on how billions of people used words in context on the internet. A side effect of this next-word prediction is that GenAI chatbots like ChatGPT can generate replies to questions in realistic language and produce clear summaries of complex texts.
Led by researchers at 好色tv Langone Health, the current paper explores the application of ChatGPT to the design of a software program that uses text messages to counter diabetes by encouraging patients to eat healthier and get exercise. The team tested whether AI-enabled interchanges between doctors and software engineers could hasten the development of such a personalized automatic messaging system (PAMS).
In the current study, 11 evaluators in fields ranging from medicine to computer science successfully used ChatGPT to produce a version of the diabetes tool over 40 hours. An original, non鈥揂I-enabled effort had required more than 200 programmer-hours.
鈥淲e found that ChatGPT improves communications between technical and nontechnical team members to hasten the design of computational solutions to medical problems,鈥 said study corresponding author Danissa Rodriguez, PhD, MS, assistant professor in the at 好色tv Langone and a member of its . 鈥淭he chatbot drove rapid progress throughout the software development life cycle, from capturing original ideas, to deciding which features to include, to generating the computer code. If this proves to be effective at scale it could revolutionize healthcare software design.鈥
Artificial Intelligence as Translator
Generative AI tools are sensitive, say the study authors, and asking a question of the tool in two subtly different ways may yield divergent answers. The skill required to frame the questions asked of chatbots in a way that elicits the desired response, called prompt engineering, combines intuition and experimentation. Physicians and nurses, with their understanding of nuanced medical contexts, are well positioned to engineer strategic prompts that improve communications with engineers, and they can do this without learning to write computer code.
However, these design efforts鈥攊n which care providers, the would-be users of a new software, seek to advise engineers about what it must include鈥攃an be compromised by attempts to converse using 鈥渄ifferent鈥 technical languages. In the current study, the clinical members of the team were able to type their ideas in plain English, enter them into ChatGPT, and ask the tool to convert their input into the kind of language required to guide coding work by the team鈥檚 software engineers. AI could take software design only so far before human software developers were needed for final code generation, but the overall process was greatly accelerated, say the authors.
鈥淥ur study found that ChatGPT can democratize the design of healthcare software by enabling doctors and nurses to drive its creation,鈥 said senior study author Devin Mann, MD, director of the HiBRID Lab and strategic director of digital health innovation within 好色tv Langone鈥檚 Medical Center Information Technology (MCIT). 鈥淕enAI-assisted development promises to deliver computational tools that are usable, reliable, and in line with the highest coding standards.鈥
Along with Dr. Rodriguez and Dr. Mann, study authors from the Department of Population Health at 好色tv Langone were ; Beatrix Brandfield-Harvey; Lynn Xu, MPH; Sumaiya Tasneem, MPH; and Defne Levine, MPH. Javier Gonzalez, technical lead in the HiBRID Lab, was also a study author. This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases grant 1R18DK118545-01A1.
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