Central to the care and treatment of cancer is the accurate and timely diagnosis. Healthcare experiences many inefficiencies, especially in the pathology of diagnosing cancer. AI promises to use the mind-boggling amount of data being collected every day to train the algorithms to improve diagnosis and prognosis of cancer.
It is estimated that almost 80 percent of decisions made with regard to patient care are informed by pathology. Despite being highly trained professionals, pathologists are prone to errors. Statistics show that misdiagnosis and other inefficiencies cost the U.S economy $750B annually.
AI stands to transform cancer care by eliminating human errors in pathology. By automating the process, AI ensures a robust and accurate diagnosis as well as prognosis of cancer. Big data in healthcare is a huge opportunity for AI. Laboratory tests, genomics, imaging, as well as electronic health records will assist AI in leveraging the technologies available to better inform cancer treatment.
Already, AI is making an impact on the treatment of lung cancer patients. Stanford University researchers have developed have developed an algorithm to accurately predict the prognosis of non-small cell lung cancer cells. This is a major breakthrough that could provide a rapid and objective prediction of survival for many cancer patients.
Another project has been initiated by CancerLinQ. The project aims at collecting data from all cancer patients in the US, collate and make it available in the hope that AI users will discover interesting patterns that will lead to more insights.
However, AI is not entirely the panacea of cancer treatment. Healthcare is complex because it interacts uniquely with data, machines, patients, and science, AI innovations need to address the fundamental issues such as access, cost, and quality.
AI applications in cancer treatment are diverse. The bottom line is automation of various procedures required in the treatment of cancer – from classification, discovery of nonobservable correlation, and other meaningful clinical outcomes of cancer.
The gradual integration of AI into cancer treatment will revolutionize and improve the treatment outcome and care of cancer patients.