ChatGPT Extracts Data for Ischaemic Stroke Almost Perfectly

In an ischaemic stroke, an artery in the brain is blocked by blood clots and the brain cells can no longer be supplied with blood as a result. Doctors must therefore act quickly and unblock the artery with the help of catheters. During the so-called mechanical thrombectomy, a lot of data has to be recorded and then transferred to various registers. Dr Nils Lehnen, senior physician at the Clinic for Diagnostic and Interventional Neuroradiology and Paediatric Neuroradiology at the University Hospital Bonn (UKB), has now discovered in a study that ChatGPT could be a great help in this data transfer. The results have now been published in the specialist journal "RADIOLOGY".

When did the patient arrive, when was a CT scan performed, when was the first puncture, when could the blood flow be restored,... During mechanical thrombectomy, a range of data must be recorded in the patient report and then manually transferred to various registers for the clinical outcome and for prospective studies. "This is a labour-intensive task that is also prone to transcription errors," says Dr Nils Lehnen, who also conducts research at the University of Bonn. "We therefore asked ourselves whether an AI such as ChatGPT could perform this transfer faster and possibly even more reliably."

In radiology, ChatGPT is already being tested in various procedures - for example, in the simplification of reports or in answering patient questionson breast cancer screening. However, whether ChatGPT can correctly extract data from free-text reports of a mechanical thrombectomy for a database and simultaneously generate clinical data was previously unexplored and was the research objective of this new study.

Dr Lehnen's research group first created a German prompt for ChatGPT and tested it on 20 reports in order to identify errors and subsequently adapt the prompt. After the correction, the data extraction using ChatGPT was tested on 100 internal reports from the UKB. For optimal comparison, an experienced neuroradiologist also compiled the results without seeing the ChatGPT evaluation. The researchers then compared the results and found that ChatGPT had correctly extracted 94 per cent of data entries and no post-processing was required. The researchers only considered the ChatGPT data entries that exactly matched that of the expert to be correct. Any deviations, such as additional symbols, punctuation marks or synonyms, were categorised as incorrect.

To validate these results, the researchers tested a further 30 external reports with the same prompt. ChatGPT achieved 90 per cent correct data entries.

"This suggests that ChatGPT could be an alternative to manually retrieving this data," says Dr Lehnen. "However, the reports and the prompt were only created by us in German, so the results of our study may need to be confirmed for other languages. In addition, we still observed poor results for certain data points, which shows that human supervision is still needed. However, we expect that further optimisation of the prompt will further improve the results and that ChatGPT can make work easier in this area in the future."

Lehnen NC, Dorn F, Wiest IC, Zimmermann H, Radbruch A, Kather JN, Paech D.
Data Extraction from Free-Text Reports on Mechanical Thrombectomy in Acute Ischemic Stroke Using ChatGPT: A Retrospective Analysis.
Radiology. 2024 Apr;311(1):e232741. doi: 10.1148/radiol.232741

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

Improved Cough-Detection Tech can Help w…

Researchers have improved the ability of wearable health devices to accurately detect when a patient is coughing, making it easier to monitor chronic health conditions and predict health risks such...

Multimodal AI Poised to Revolutionize Ca…

Although artificial intelligence (AI) has already shown promise in cardiovascular medicine, most existing tools analyze only one type of data - such as electrocardiograms or cardiac images - limiting their...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...