New AI cancer detection tool to expedite pancreatic cancer testing

Investigators at Harvard Medical School and the University of Copenhagen, in collaboration with VA Boston Healthcare System, Dana-Farber Cancer Institute, and the Harvard T.H. Chan School of Public Health have developed an AI-based population screening that can expedite the diagnosis of pancreatic cancer. This groundbreaking tool promises to revolutionise cancer diagnosis and treatment, offering patients a faster, more accurate diagnosis and a better chance of survival.

The findings, of the new AI tool, were published on May 8 in the peer-reviewed journal, Nature Medicine. The AI algorithm is based on machine learning algorithms that can analyse large amounts of medical data to identify patterns and predict outcomes. It was trained on two separate data sets totalling 9 million patient records from Denmark and the United States.

Cancer is one of the leading causes of death around the world. According to the World Health Organisation, about 10 million deaths or nearly one in six deaths can be attributed to cancer every year. Cancer can be fatal but there is hope for the disease to be cured if one is able to detect and treat it early.

At present, there are no population-based tools to broadly screen for pancreatic cancer but those with a family history and certain genetic mutations are at high risk for it. People with these known predispositions should be screened in a targeted fashion. However, such targeted screenings can likely miss out on other cases that fall outside of those categories.

Using the innovative AI tool, combinations of disease codes and the timing of their occurrence can be used to predict which patients are most likely to develop pancreatic cancer in the future even if their present symptoms and disease codes are not directly related to or stemming from issues with their pancreas.

Chris Sander, study co-senior investigator and a faculty member in the Department of Systems Biology in the Blavatnik Institute at HMS shared: "One of the most important decisions clinicians face day to day is who is at high risk for a disease, and who would benefit from further testing, which can also mean more invasive and more expensive procedures that carry their own risks.

"An AI tool that can zero in on those at highest risk for pancreatic cancer who stand to benefit most from further tests could go a long way toward improving clinical decision-making."

Another recent medical AI tool related to identifying cancer cells is the Libra study which uses a technique called radiomics, an image analysis technology that can be used to detect information not spotted by the human eye to detect lung cancer. The researchers used 900 CT scans of people with large lung nodules to develop the algorithm that helps the AI tool make predictions related to cancerous growths in the body. This is spearheaded by experts at the Royal Marsden NHS Foundation Trust, the Institute of Cancer Research, London, and Imperial College London.

At the Southend Hospital, a surgeon recently employed a robotic device to assist in a surgical operation. Matteo Massanova, consultant urologist and robotic surgeon, used a robotic arm controlled through a console to allow for enhanced precision and control during the procedure.

After the successful procedure, doctors are now exploring the feasibility of using the Da Vinci Surgical System with procedures that tackle other forms of cancer. With operations taking place at Southend Hospital, patients across mid and south Essex can expect ongoing development in testing robotic devices in other types of surgeries.

With the number of people needing care growing quickly, researchers are racing to bring to life artificial intelligence that can take over some of the tasks carried out today by nurses, carers and doctors.