ChatGPT fails at heart risk assessment

Despite ChatGPT's reported ability to pass medical exams, new research indicates it would be unwise to rely on it for some health assessments, such as whether a patient with chest pain needs to be hospitalized.

In a study involving thousands of simulated cases of patients with chest pain, ChatGPT provided inconsistent conclusions, returning different heart risk assessment levels for the exact same patient data. The generative AI system also failed to match the traditional methods physicians use to judge a patient’s cardiac risk. The findings were published in the journal PLOS ONE.

"ChatGPT was not acting in a consistent manner," said lead author Dr. Thomas Heston, a researcher with Washington State University's Elson S. Floyd College of Medicine. "Given the exact same data, ChatGPT would give a score of low risk, then next time an intermediate risk, and occasionally, it would go as far as giving a high risk."

The authors believe the problem is likely due to the level of randomness built into the current version of the software, ChatGPT4, which helps it vary its responses to simulate natural language. This same randomness, however, does not work well for healthcare uses that require a single, consistent answer, Heston said.

"We found there was a lot of variation, and that variation in approach can be dangerous," he said. "It can be a useful tool, but I think the technology is going a lot faster than our understanding of it, so it's critically important that we do a lot of research, especially in these high-stakes clinical situations."

Chest pains are common complaints in emergency rooms, requiring doctors to rapidly assess the urgency of a patient's condition. Some very serious cases are easy to identify by their symptoms, but lower risk ones can be trickier, Heston said, especially when determining whether someone should be hospitalized for observation or sent home and receive outpatient care.

Currently medical professionals often use one of two measures that go by the acronyms TIMI and HEART to assess heart risk. Heston likened these scales to calculators with each using a handful of variables including symptoms, health history and age. In contrast, an AI neural network like ChatGPT can assess billions of variables quickly, meaning it could potentially analyze a complex situation faster and more thoroughly.

For this study, Heston and colleague Dr. Lawrence Lewis of Washington University in St. Louis first generated three datasets of 10,000 randomized, simulated cases each. One dataset had the seven variables of the TIMI scale, the second set included the five HEART scale variables and a third had 44 randomized health variables. On the first two datasets, ChatGPT gave a different risk assessment 45% to 48% of the time on individual cases than a fixed TIMI or HEART score. For the last data set, the researchers ran the cases four times and found ChatGPT often did not agree with itself, returning different assessment levels for the same cases 44% of the time.

Despite the negative findings of this study, Heston sees great potential for generative AI in health care - with further development. For instance, assuming privacy standards could be met, entire medical records could be loaded into the program, and an in an emergency setting, a doctor could ask ChatGPT to give the most pertinent facts about a patient quickly. Also, for difficult, complex cases, doctors could ask the program to generate several possible diagnoses.

"ChatGPT could be excellent at creating a differential diagnosis and that's probably one of its greatest strengths," said Heston. "If you don’t quite know what's going on with a patient, you could ask it to give the top five diagnoses and the reasoning behind each one. So it could be good at helping you think through a problem, but it’s not good at giving the answer."

Heston TF, Lewis LM.
ChatGPT provides inconsistent risk-stratification of patients with atraumatic chest pain.
PLoS One. 2024 Apr 16;19(4):e0301854. doi: 10.1371/journal.pone.0301854

Most Popular Now

Herefordshire and Worcestershire Health …

Herefordshire and Worcestershire Health and Care NHS Trust has successfully implemented Alcidion's Miya Precision platform to streamline bed management workflow across seven community hospitals in Worcestershire. The trust delivers community...

With Huge Patient Dataset, AI Accurately…

Scientists have designed a new artificial intelligence (AI) model that emulates randomized clinical trials at determining the treatment options most effective at preventing stroke in people with heart disease. The model...

A Shortcut for Drug Discovery

For most human proteins, there are no small molecules known to bind them chemically (so called "ligands"). Ligands frequently represent important starting points for drug development but this knowledge gap...

New Horizon Europe Funding Boosts Europe…

The European Commission has announced the launch of new Horizon Europe calls, with a substantial funding pool of over €112 million. These calls are aimed primarily at pioneering projects in...

Cleveland Clinic Study Finds AI can Deve…

Cleveland Clinic researchers developed an artficial intelligence (AI) model that can determine the best combination and timeline to use when prescribing drugs to treat a bacterial infection, based solely on...

New AI-Technology Estimates Brain Age Us…

As people age, their brains do, too. But if a brain ages prematurely, there is potential for age-related diseases such as mild-cognitive impairment, dementia, or Parkinson's disease. If "brain age...

Radboud University Medical Center and Ph…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Radboud University Medical Center have signed a hospital-wide, long-term strategic partnership that delivers the latest patient monitoring...

GPT-4, Google Gemini Fall Short in Breas…

Use of publicly available large language models (LLMs) resulted in changes in breast imaging reports classification that could have a negative effect on patient management, according to a new international...

ChatGPT fails at heart risk assessment

Despite ChatGPT's reported ability to pass medical exams, new research indicates it would be unwise to rely on it for some health assessments, such as whether a patient with chest...

Study Shows ChatGPT Failed when Challeng…

With artificial intelligence (AI) poised to become a fundamental part of clinical research and decision making, many still question the accuracy of ChatGPT, a sophisticated AI language model, to support...

Virtual Reality Shows Promise in Fightin…

A new study published in JMIR Mental Health sheds light on the promising role of virtual reality (VR) in treating major depressive disorder (MDD). Titled "Examining the Efficacy of Extended...

AXREM and Highland Marketing Partner to …

AXREM represents member companies that collectively provide UK hospitals with most of their diagnostic medical imaging technology, and radiotherapy equipment. The association has seen substantial growth in recent years, with membership...