A diagnostic prediction model for colorectal cancer in elderlies via internet of medical things

Asghari, Parvaneh

Internet of Medical Things (IoMT) and embedded systems have improved the healthcare systems by enabling remote monitoring the patients’ health conditions anywhere and anytime especially during novel COVID-19 pandemic. In this paper, an IoT-based predicting model is proposed to predict colorectal cancer (CRC) in elderlies. It provides a CRC predicting model for the involved medical team to continuously trace an elderly’s biological indicators using smart wearable embedded systems and medical IoT devices. In this model, vital medical data is collected by IoMT devices and sensors, then analytical information is derived via machine learning (ML) methods for early CRC diagnosis and elderly’s health parameters changes. The experimental results confirm that the suggested model meets the proper accuracy of predicting the CRC in aged people.