Artificial Intelligence and the Future of Cancer Diagnosis

Although it was once thought of as futuristic sci-fi or a mystical art, artificial intelligence (AI), the simulation of expert human reasoning, has come a long way from its humble beginnings. Today, AI is evolving every aspect of medicine through everything from informatics to nanorobotics for drug delivery. While these breakthrough technologies are creating exciting new possibilities for treatments, many have worried that AI will one day replace medical professionals. Yet it seems that instead AI will expand opportunities in the medical field, rather than diminish. Many researchers believe that in the foreseeable future, AI will not replace human physicians, but instead assist physicians to make better clinical decisions.

Artificial Intelligence (AI)

Before AI systems can be deployed in healthcare applications, AI devices need to be trained to recognize patterns in data and understand when a particular event or action is to be performed. This is how a machine processes large amounts of data quickly and continuously learns. Medical AI is trained using the data that is generated through various clinical activities including screening, diagnosis, and treatment. These activities generate significant clinical data in multiple forms, including demographics, medical notes, electronic recordings from medical devices, physical examinations, clinical lab observations, and images. AI uses its coded algorithm to rapidly recognize patterns in the data and make predictions on similar inputs. AI learns with each new piece of data, getting exponentially smarter over time.

Artificial Intelligence in Medicine

Clinics and hospitals using AI applications are seeing immediate gains in reducing clinical error. These improvements span across critical tasks such as patient flow optimization, medical imaging and diagnostics, electronic health records automation, predictive analytics, and event risk analytics. Each advancement adds up, stacking the ways that medical professionals are now empowered to improve patient outcomes. Perhaps most importantly, AI removes the subjectivity and variability from exams so that doctors are able to objectively diagnose their patients -- oftentimes catching disease earlier than conventional methods. These earlier diagnoses can make a difference in the range of appropriate treatment options available to a patient, making it more likely for them to pursue treatment and heal.

The Future of Cancer Diagnosis

It is well known that early detection is the key to successful cancer treatment. Without AI, medical professionals are working under often subjective and variable conditions. Although skilled radiologists can spot telltale signs of abnormal growth, errors do occur. Some people receive a false positive report where there is no malignant lesion, while others receive a false negative report in spite of the malignant lesion being present. Both of these scenarios create distress and can lead to delays in treatment, especially in cases where patients receive false negative reports. That’s why the diagnostic process is the ideal activity to optimize. When these issues are avoided, cancer can be detected earlier and treated sooner.

The future of cancer diagnosis will focus on detecting whether a lesion or tumor is malignant or benign without the need for an invasive procedure such as a biopsy. Since each type of cancer interacts with its surroundings differently, algorithms will need to overcome an assortment of problems to successfully diagnose each kind of disease at this level. We’re already seeing important breakthroughs in diagnosing cancers of the breast, cervix, lungs, and ovaries, among others.

Conclusion

We will continue to innovate and expand AI’s vital role in advancing medicine. These advancements will empower physicians to diagnose and treat disease earlier, making it possible to improve patient outcomes.