Utilizing Artificial Intelligence to Improve Patient Diagnosis

According to recent research, artificial intelligence (AI) can be used as an aid to assist lung doctors interpret respiratory symptoms accurately and make a correct diagnosis.

"Pulmonary function tests provide an extensive series of numerical outputs and their patterns can be hard for the human eye to perceive and recognize; however, it is easy for computers to manage large quantities of data like these and so we thought AI could be useful for pulmonologists,” Marko Topalovic, PhD, postdoctoral researcher at the Laboratory for Respiratory Diseases, Catholic University of Leuven (KU Leuven), Belgium, explained. “We explored if this was true with 120 pulmonologists from 16 hospitals. We found that diagnosis by AI was more accurate in twice as many cases as diagnosis by pulmonologists. These results show how AI can serve as a second opinion for pulmonologists when they are assessing and diagnosing their patients."

 For the study, the researchers used historical data from 1430 patients from 33 Belgian hospitals. An expert panel of pulmonologists then assessed the data and measured it against GOLD standard guidelines from the European Respiratory Society and the American Thoracic Society. 

"When training the AI algorithm, the use of good quality data is of utmost importance," explained Dr Topalovic. "An expert panel examined all the results from the pulmonary function tests, and the other tests and medical information as well. They used these to reach agreement on final diagnoses that the experts were confident were correct. These were then used to develop an algorithm to train the AI, before validating it by incorporating it into real clinical practice at the University Hospital Leuven. The challenging part was making sure the algorithm recognized patterns of up to nine different diseases."

The 120 pulmonologists made 6000 interpretations of PFT data from 50 randomly selected patients, and then AI examined the same data. The researchers took the results from both the pulmonologists and AI and measured them against the GOLD guidelines in the same way as during the development of the algorithm.

According to the findings, the researchers determined that the interpretation of the PFTs by the pulmonologists matched the guidelines in 74% of cases (with a range of 56-88%), but the AI-based software interpretations perfectly matched the guidelines (100%). Further, the doctors correctly diagnosed the primary disease in 45% of cases, while AI was able to correctly diagnose primary disease in 82% of cases.

"Nowadays, we trust computers to fly our planes, to drive our cars and to survey our security,” Dr Topalovic said. “We can also have confidence in computers to label medical conditions based on specific data. The beauty is that, independent of location or medical coverage, AI can provide the highest standards of PFT interpretation and patients can have the best and affordable diagnostic experience.”

According to Dr Topalovic, the next step is the get more hospitals to adopt the use of this technology and investigate transferring the AI technology to primary care in order to help general practitioners make correct diagnoses and referrals.

This research was presented at the European Respiratory Society International Congress.

—Julie Gould

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