This chart appeared in a recent Digital Health Briefing, the subscriber-only daily newsletter from Insider Intelligence.
| | The chart below appeared recently in our exclusive Digital Health Briefing, a daily email newsletter available only to subscribers. Right now, you can try the Briefing for just $1! Read on for a preview of the content you can expect as a Briefing subscriber. | | | | The AI medical image analysis company, which focuses on respiratory conditions, earned a license permitting it to develop an AI tool to analyze lung scans and more efficiently detect the progression of cystic fibrosis (CF) in children, according to MobiHealthNews. Thirona's LungQ software will help clinicians detect and determine the extent of CF lung disease. CF is a rare condition without a cure that affects 70,000 patients globally—most of whom are diagnosed in early childhood.
AI-automated lung scans could help hospitals cut back on the time and expertise needed to detect abnormalities. CT scans are used to monitor the progression of CF, and a scoring method for analyzing children's scans—called PRAGMA-CF—is time-consuming and requires considerable clinician training, per Thirona. Thirona's new tool automates the PRAGMA-CF technique, allowing doctors to use it without extensive training and cutting down the turnaround time for receiving results.
Doctors see the value in diagnostic AI—and developers have been rushing to roll out algorithms that can aid in coronavirus diagnoses. Hospital leaders are optimistic about the power AI holds in improving the diagnostic process: 72% of healthcare leaders said the top benefits of deploying AI are improving diagnostic accuracy and reducing time associated with diagnoses, according to a 2019 Definitive Healthcare survey. However, physician skepticism over how AI solutions come to their conclusions may hinder clinical implementation. With new diagnostic AI tools hitting the market, developers can win over worried doctors by being as transparent as possible about the data algorithms were trained on and the sample size of trials. | |  | | | |
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