AI vs Radiologists: can AI surpass doctors in reporting accuracy?

VILNIUS, Lithuania - Nov. 26, 2019 - PRLog -- Furthermore, AI reports were more accurate in 5% of analyzed patient cases. The study was undertaken using Oxipit (https://www.oxipit.ai) ChestEye AI imaging suite. The full study titled The full study titled "Judging the Accuracy and Clinical Validity of Deep Learning-Generated Test Reports" will be presented at the annual Radiological Society of North America conference in Chicago later this year.

The study led by Dr Vasanth Venugopal aimed to evaluate the accuracy and clinical validity of AI-generated reports of chest X-rays. Additional aim of the study was to identify elements of "hedging" - a practice of using inconclusive, defensive, non-committal diagnosis statements in order to hedge against mistakes or potential legal threats - in clinical reports.

A set of 297 retrospective chest X-ray images was used in the study. The images were analyzed by Oxipit ChestEye and AI generated reports compared to the ones produced by a radiologist. Final report comparison and diagnosis validation was conducted by a radiologist with 9 years of clinical experience.

In 236 (79%) cases, algorithm-generated reports were found to be as accurate as the radiologists' reports. In 16 (5%) cases, algorithm generated reports were found to be either more accurate or more clinically appropriate. In 18 (6%) cases, the algorithm made significant diagnostic errors and in 27 (9%) cases, the algorithm-generated reports were found to be clinically inappropriate or insufficient even though the significant findings were correctly identified and localised.

"Oxipit ChestEye was designed as a productivity and second-opinion tool to aid the work of radiologists. The evaluation that nearly 80% of preliminary reports generated by our software were clinically accurate to be deemed as final reports, and in 5% cases - even more accurate than the ones produced by a radiologist, is an inspiring validation of current capabilities of AI diagnostics" - notes Dr N. Ramanauskas.

In the words of Dr N. Ramanauskas, even two radiologists can have differing opinions over a particular X-ray report.

"Therefore aiming for 100% correlation to radiologist reports is unrealistic. However, with constant improvement of deep learning algorithms and innovations in medical imaging field, a radiologist working with the help of AI can help to reduce interpersonal subjectivity and greatly increase the quality of the reports while helping the radiologists become more efficient." - notes Dr N. Ramanauskas.

The study also found that preliminary reports produced by Oxipit ChestEye AI platform can reduce hedging and defensive reporting statements in radiologist reports, resulting in clearer more actionable diagnosis descriptions.