Nearly 1 in 6 deaths is attributed to cancer, making the disease a leading cause of mortality worldwide. The good news is scientific advancements and technology have made it possible to reduce fatalities by detecting cancer early. Specifically, AI as a tool in healthcare is instrumental in identifying the presence of cancer improving the chances of survival and a good outcome due to early and effective treatment.
Prompt Screening Is a Game-Changer
Technology plays an important role in the detection, treatment, and management of cancer. Basically, AI uses computers to do things that require human input. With AI, machines create algorithms to classify, analyze, and interpret data. For example, AI in healthcare will support clinicians in reviewing images and scans. The input will be used by specialist physicians to identify critical cases and avoid errors in reading and interpreting electronic health records (EHRs) providing a precise diagnosis.
AI will not take over the jobs of doctors as there will still be a need for a human touch especially when discussing a cancer prognosis. However, AI is key in early detection. According to Halamka and Cerrato, medical imaging is the most remarkable success story. Machine learning has improved the screening and diagnosis of several diseases including detection of cancers. To illustrate, machine learning systems for early detection could potentially save a lot of lives. By training an AI system to find the early stages of cancer, it can improve the outlook of the disease. When the computer finds tumors in scans of patients more accurately than trained radiologists, it gives hope to people who have the illness. It increases the chances of survival for thousands of people with the same problems because the outcome and prognosis are much better especially if the tumors are small and confined to a certain area.
Development of Sensitive AI Systems to Detect Smaller Tumors
Given the incredible opportunities provided by AI systems in healthcare, companies, universities, and other institutions are collaborating to help diagnose cancer faster and earlier. For example, a joint initiative between Northwestern University, Google, and other research institutions to identify smaller tumors is moving towards clinical adoption. Another research collaboration spearheaded by the University of Oxford with a GBP11 million funding is targeted at a research program that will employ AI to diagnose lung cancer.
The aim is to make lung-cancer screening more precise and shorter and above all, accessible to everyone. However, it is important to cultivate a good working relationship between machines and radiologists and other specialists. Without a harmonious collaboration between the doctors and the machines, it will be difficult to make cancer screening precise and accessible to everyone.
Detection of cancer is not always straightforward. However, with the help of trained and deep learning AI machines systems, it is possible to spot cancers accurately. Compared to non-AI systems, this development is expected to offer reliable and precise diagnosis that will improve the prognosis of thousands of patients.
