Artificial intelligence at work in cancer diagnosis and treatment - Gadgets Price
Artificial intelligence at work in cancer diagnosis and treatment

Despite major advances in treatment and diagnosis in recent decades, cancer is still the leading cause of death and a major barrier to extending life expectancy worldwide. The future involvement of artificial intelligence in healthcare, especially in cancer detection and treatment, is expected to take various forms, ranging from identifying a specific cancer to evaluating which therapy method can best treat that particular case. . AI promises to increase the customization of cancer care and help people live with the disease with a higher quality of life and fewer side effects.

Using artificial intelligence to improve cancer screening

To detect cancer at its most treatable stage, screenings are designed to proactively monitor patients who do not show symptoms. US Preventative Services Task Force recommends screening for breast, cervical, colorectal, and lung cancer.

Lung cancer is the world’s deadliest cancer, with a 75% death rate for those diagnosed in five years. Although tobacco use is the greatest risk factor, research shows that occupational exposure to lung carcinogens such as asbestos, beryllium, cadmium, chromium, diesel fumes, nickel, vinyl chloride and silica is increasingly relevant to the development of this disease. The outlook is significantly better when cancer is detected early.

Screening for lung cancer using computed tomography (CT) has been shown to be extremely efficient in reducing the death rate associated with the disease. It is estimated that screening can reduce this death rate by as much as 20%. However, there are still significant hurdles that limit the efficiency of CT screening. Even highly trained radiologists can miss signs of lung cancer in some scans, delaying detection and necessary therapy.

Researchers have found encouraging results using an AI algorithm to detect indicators of lung cancer on scans. Research published in JAMA Network Open found that an AI system trained to identify lung nodules on chest X-rays could improve lung cancer identification. Even more accurate than radiologists, the algorithm was found to detect cancers and malignant growths in a scan study. CT screening false positives and false negatives were also minimized by this method.

AI helps treat rare and aggressive malignancies

In a preliminary trial, AI is being used to assess patients being treated for rare cancers related to occupational exposure to asbestos — a cancer-causing mineral widely used in many industries. Scientists have created a prototype imaging system that has been shown to be successful in detecting and treating mesothelioma – a rare and deadly cancer that develops in the lining of the lungs or abdomen as a result of exposure to asbestos fibers – and has the potential to accelerate much-needed progress in diagnosis and treatment.

Patients undergoing treatment for mesothelioma could be evaluated using AI as part of a prototype imaging system that could revolutionize the way patients with the condition are cared for. The researchers investigated the feasibility of a technique for automatically identifying mesothelioma tumors and their boundaries on CT scans, a process known as image segmentation. Subsequent funding for phase two has enabled the construction of a prototype algorithm that does this using a trained AI system. This breakthrough opens the door to an AI system that can significantly increase the efficiency of clinical trials, as well as the precision and reliability of treatment response assessments in the clinic.

The effectively optimized AI program may be able to find mesothelioma on a CT scan and estimate its volume, allowing comparison with previous measurements and reducing the cost of clinical trials in the process. An important step in the development of this system is the training procedure, which requires a human to “draw” all regions of mesothelioma on each CT image to teach the AI ​​what this looks like. Phase one revealed that this procedure, known as ground truth generation, required the expertise of a mesothelioma physician with extensive knowledge of mesothelioma images and the anatomy of the chest, as it proved extremely difficult for an imaging technician to perform.

At present, survival time after diagnosis is dismal as the vast majority of people with malignant pleural mesothelioma are diagnosed at an advanced stage. Treatment options for mesothelioma, including chemotherapy, radiation, and surgery, are limited and clinical trials are critical to developing new, more effective treatments. With this AI system, clinical trials of new drugs can be performed more quickly, because it can more efficiently recognize mesothelioma on CT images.

Integrating AI technology into cancer care could improve quality of life

Treatment-related problems are common in cancer patients, resulting in a poorer quality of life, shorter survival time, and overuse of emergency care and hospital services. AI could potentially be used in the treatment of cancer patients who experience adverse effects as a result of their treatments.

Chemotherapy regimens can be improved by using AI to control drug use and predict their tolerance. AI can help doctors make the best treatment decisions, reduce unnecessary procedures, and help oncologists improve cancer treatment regimens for their patients. In the field of cancer chemotherapy, AI focuses on the interactions between drugs and patients. Among the key achievements of AI in this area are the management of chemotherapy drug use, the prediction of drug tolerance, and the optimization of chemotherapy regimens.

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