LSUS alumni's develop AI chatbot with Discord server to help with medical coding
Two Louisiana State University of Shreveport alumni have developed an innovative medical coding chatbot that is designed to reduce time and improve accuracy for medical coding.
According to LSUS, Phillip Kilgore and Keyvan Shahrdar have created an ICD code reference powered by artificial intelligence to help medical professionals sift quickly through approximately 9,000 International Classification of Diseases (ICD) codes.
“People usually go through an insane amount of training just to learn the codes,” said Kilgore. “Take something like cancer – there are potentially hundreds of ICD codes for cancer, but with this tool, you can describe the symptoms, and the bot will produce a list of codes that are related to what you’re describing."
He continued by saying, "our goal with this software is to provide a reliable tool that enables medical professionals to rapidly access accurate ICD codes, freeing up more time for patient care."
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This code list can be viewed digitally on the Discord server or imported into an Excel spreadsheet for download.
Shahrdar said, “This is the first of its kind Discord server that’s able to use a chatbot to return ICD codes. As an educator and entrepreneur, I'm thrilled to introduce this advanced AI tool to the healthcare community."
According to LSUS, the medical coding chatbot is built upon the ChatBotCPA framework, a sophisticated conversational process automation (CPA) platform. This platform allows the chatbot to interpret medical terminologies and context, enabling the chatbot to reference the most relevant ICD codes in response.
Kilgore, the chief technology officer for Shahrdar Enterprises, has experienced the complexity of the medical coding while he worked on projects involving massive databases of cancer diagnoses, which required ICD codes to navigate, to pinpoint specific forms of cancer.
Navigating ICD codes could impact medical research and insurance underwriting along with improving patient care. “Patients will want their doctors to accurately summarize the nature of their disease, and this has a research benefit as well because we’re improving the accuracy of how diseases and comorbidities are coded and recorded," said Kilgore.
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Makenzie Boucher is a reporter with the Shreveport Times. Contact her at mboucher@gannett.com.
This article originally appeared on Shreveport Times: LSUS alumni's develop AI chatbot to help with medical coding
