The use of AI in cancer detection is fundamentally changing the landscape, compared to human perception, with significant advances in diagnostic accuracy and the time taken for diagnosis. New advancements mean AI models can now spot more than 170 types of cancer, giving people an earlier chance of treatment and a much better chance of survival.
The value of AI in oncology is in its capacity to understand and analyze large and complicated datasets — from medical imaging such as mammograms, CT scans and MRIs to genomic information, pathology reports and even details of a patient’s lifestyle.
Where human radiologists or pathologists can be hampered by fatigue or subjective judgment, AI algorithms can scan these datasets for subtle patterns and nuances that may be imperceptible to the naked eye. This function is critical for diagnosing cancer in its earliest stages when it is typically easiest to treat.
For instance, AI-enabled programmes are already more accurate at interpreting mammograms to detect breast cancer and result in fewer false positives and negatives. In lung cancer, which is frequently diagnosed at a late stage, AI technology is playing an important role in detecting small nodules in CT images of the lungs, resulting in early detection and treatment.
In addition to popular cancers, these sophisticated AI systems are being taught using an array of data to be able to identify specific markers for a variety of cancers, even including rare diseases which often cause difficulty in diagnosis due to their complexity and lack of medical expertise.
This jump in technology isn’t just about accuracy, but about reach. AI-based diagnostic systems are of great potential for underserved, remote areas where there is a general lack of trained medical personnel. AI can close geographic gaps by facilitating remote interpretation of images and data, to further ensure that patients around the world receive a timely diagnosis and appropriate treatment.
Remaining challenges in ethical, transparent, and ongoing-validated use of these powerful AI tools notwithstanding, their impact on oncology is unmistakable.
The ability to identify and respond to 170-plus types of cancer with greater accuracy marks the advent of a new age in the war against cancer, a battle in which technology is empowering clinicians to act more quickly and knowledgeably, and where patient care and survival rates are improving.
