Breast Cancer Detection using machine learning and IoT: A Review

Breast cancer is the most common cancer between women not men which caused byabnormal and rapid growth of breast cells. It is crucial to detect cancerous cells at the earlystage to reduce the rate of cancer induced mortality. Early detection and diagnosis can savethe lives of breast cancer patients. Among of various diagnosis platforms, imagingtechniques are main diagnosis approaches which could provide valuable data on patientswith breast cancer. There are several imaging methods which can detect breast tumors atearly stages such as mammography, thermography, CT, ultrasonography,Histopathological and etc. Machine learning (ML) has become a major part of medicalimaging research. The advancements in the field of ML have led to more intelligent andself-reliant computer-aided diagnosis (CAD) systems. Internet of medical things (IoMT) isan innovative mean of amalgamating systems and applications to connect with thehealthcare services and patient tracking and monitoring sources. It can completely changethe working layout of the healthcare facilities while detecting and predicting cancers witha superior level of care and satisfaction. This paper aims to review the impact of IoTsystems for detecting early-stage breast cancer using imaging and machine learningapproaches.

Keywords:

IoT , IoMT , Breast Cancer , Machine Learning , Image Processing , Cancer Detection