Cancer manifests itself in a variety of ways as the disease progresses and requires special attention in providing individual treatment and assessing the subsequent response, resulting in a particularly challenging context for medical decision-making. Artificial intelligence (AI) is gaining traction in biomedical research and healthcare, particularly in cancer research and oncology, where the potential applications are limitless. These include cancer detection and diagnosis, subtype categorization, therapy optimization, and the identification of novel therapeutic targets in the drug development process.
Artificial Intelligence and Early Cancer Detection
Cancer, unlike other illnesses, must be treated at different stages, which is mostly owing to detection gaps. This is an area wherein artificial intelligence has the potential to provide significant value. AI technology may aid in the detection of precancerous lesions in tissues, boosting the sensitivity of cancer screening tests. AI-powered technologies may assist radiologists in visually analyzing images and detecting these worrisome lesions. This method not only saves radiologists time but also allows them to discover minute lesions that would otherwise go undetected.
An AI algorithm may be able to detect indications of lung cancer on CT scans a year before they can be identified using conventional methods, according to a new study presented at the European Respiratory Society International Congress. The researchers trained their AI using CT images of 888 individuals who had previously undergone radiological examination to detect worrisome growths. They then tested it on a new set of scans obtained from 1,179 people enrolled in a lung screening trial with a three-year follow-up period, during which 177 instances of lung cancer were discovered. The AI successfully identified 172 of the 177 malignancies, achieving a detection rate of 97%, with the instances it missed often being those in the middle of the chest, which is more difficult to detect.
Due to the extended latency periods associated with many illnesses, the relationship between occupational exposure and cancer is sometimes not recognized for decades. AI can also deliver objective and effective information to physicians, reducing their burden as well as the rates of missing and misdiagnosed.
Additionally, given the low survival rates associated with some malignancies – for instance, mesothelioma, a rare and deadly cancer caused by asbestos exposure, is highly lethal, with a 5-year survival rate of 10% – AI may be the panacea that many patients have hoped for.
Aside from lung cancer and mesothelioma, researchers are working on strategies to detect and diagnose breast cancer, kidney cancer, colorectal cancer and brain tumors, to mention a few. Given the rapid pace of research in this sector, it seems that the potential for AI in cancer is enormous.
AI To Forecast Cancer Progression
Artificial intelligence can aid in cancer prognosis. AI is capable of detecting pre-existing tumors and identifying those at high risk of developing the illness prior to its onset. This enables clinicians to keep a close eye on these patients and intervene quickly if the circumstances call for it. Aside from cancer detection, AI can also predict how malignancies progress and evolve, which might possibly assist physicians in devising effective therapies for individual patients as well as influencing the future treatment process. In addition, early intervention boosts a patient’s chances of survival since cancer is defeated before it has had the opportunity to establish a resistant immune response.
A research team headed by the University of Edinburgh, and the Institute of Cancer Research in London (ICR) developed a technique able to identify patterns in DNA mutation inside malignant cells, which they then used to predict future genetic alterations. In addition, the scientists found a relationship between certain sequences of recurring cancer mutations and survival outcomes. They have also devised a novel technology that may be used to share tumor information amongst individuals who have comparable conditions. By identifying recurrent patterns and correlating them to known oncology data, scientists might possibly forecast the future direction of tumor growth.
AI in Novel Oncology Drug Development and Precision Therapy
One of today’s most promising cancer treatments is immunotherapy. Patients may be able to defeat difficult-to-remove tumors by using the body’s own immune system to fight them. The existing immunotherapy alternatives, on the other hand, are only effective in a limited percentage of patients, and oncologists have yet to develop a clear and accurate way of determining which individuals would benefit from this treatment. A new generation of machine learning algorithms, as well as their capacity to synthesize very complicated information, may be able to highlight new possibilities for tailoring treatments to each individual’s distinct genetic composition.
AI may have a substantial influence on a cancer patient’s entire therapy, particularly in the realm of precision medicine. Precision medicine, often known as personalized medicine, enables clinicians to select from a set of choices to determine which one is most likely to benefit the patient. This is based on data from the patient’s current health state and illness history. These approaches also may lead to the development of novel drugs as well.
Cancer is a chronic yet curable illness, when detected early and healthcare expenditures are affordable. Air pollution, radiation, chemical and pesticide exposure, and occupational exposure to carcinogens all increase a person’s risk of developing cancer. According to the CDC, cancer and heart disease are the leading causes of death in the United States’ middle-aged population, and it could soon become the leading cause of death overall as the number of individuals diagnosed with and dying from cancer climbs. This is concerning because our healthcare systems are already stretched thin. The pandemic has highlighted how, with the emergence of new and emerging illnesses, healthcare systems’ responses to chronic diseases may take a second seat. This is where emerging technologies like artificial intelligence can make a major difference. While AI has made significant strides in a variety of fields, the technology has been making inroads into healthcare, most notably in medical oncology.