A new AI technology can identify cancer types and genetic changes in lung tumors, potentially speeding up the diagnosis and treatment process.
According to ANSI, this tool can use machine learning to analyze images of patients’ lung tumors and differentiate adenocarcinoma and squamous cell carcinoma with 97 percent accuracy. Interestingly enough, the study that tested this technology showed that the patients that the AI often mistyped were the ones that pathologists had also misdiagnosed, showing the difficulty in differentiating between these two lung cancer types.
AI is continuing to become more accepted in the medical field, as it creates opportunities for the medical field to be expand to underdeveloped areas and potentially improve outcomes of patients. This acceptance is relatively new, with the FDA issued their first approval of marketing a technology that uses AI to detect diabetes-related eye problems in 2018.
While general AI standards have been around for a while, standards for AI in healthcare are in recent development along with the technology. AAMI recently released a position paper on the importance of standardization of AI in healthcare. “The emergence of artificial and machine learning in healthcare: Recommendations to support governance and regulation” analyzes AI standardization in healthcare techniques and provides recommendations for future standardization activities.