An exciting, new application of AI in healthcare is detecting tumor regrowth accurately, which can help provide timely medical assistance and save human lives.
Cancer is one of the biggest illnesses plaguing humankind today. While several treatments can detect and remove tumors, there are still chances that the tumor might grow back after undergoing the treatment. Late or no detection of the regrowth tumor can again lead to severe complications, including death. Thus, early detection is necessary to ensure that patients get the right medical assistance at the right time.
Using technologies like machine learning and AI in healthcare is already helping solve numerous issues. One of the most exciting and life-saving applications is accurately detecting the likelihood of tumor regrowth in cancer patients. This can revolutionize the surveillance of cancer patients, help provide timely treatment and significantly increase their chances of survival.
Use of AI in Healthcare for Tumor Regrowth Detection
Monitoring patients after providing them chemotherapy is essential as it ensures immediate addressal if there is any tumor regrowth. Currently, medical professionals rely on traditional detection methods. These include analyzing the original spread of cancer and the tumor size to predict the future recurrence of the tumor. Patients are required to do multiple follow-ups, which is costly and time-consuming. Most importantly, the prediction accuracy is very low, which makes the process highly inefficient.
Researchers have now developed an AI tool that can detect tumor regrowth in patients earlier and with high accuracy. This ensures that they receive the necessary treatment on time, which can help save their lives. Additionally, this method reduces the number of hospital visits and scans otherwise required for detecting tumor regrowth. The AI tool helps save time, money and resources for both patients as well as doctors.
The AI tool was used in analyzing data, such as the individual’s age, cancer history, treatment, gender, radiotherapy intensity, BMI, etc., in addition to clinical data from non-cell small lung cancer (NSCLC) patients treated at various hospitals in the UK. Based on the analysis, it determined the likelihood of tumor recurrence and other factors like the period before the recurrence and the chances of overall survival after two years of treatment. This AI tool was superior to the TNM stage and performance status in predicting recurrence and OS.
Sumeet Hindocha, the study lead, called the study an exciting first step towards rolling out the tool to guide the post-treatment surveillance of cancer patients on a national and international level. He also added that since such patient data can be easily accessed, the methodology can be replicated across different health systems.
Using AI in healthcare for cancer regrowth detection is a big step in timely detection and providing medical assistance to such patients. It provides better results than traditional methods and helps save time, money, and resources. This is going to revolutionize cancer treatment and help save countless lives.
