Abstract:Advancements in wireless communication and integrated circuit technology has increased the importance of WBAN. WBAN,s provide real time health monitoring and health updates of the patient to the physician for a longer period of time. IMD"s are usually used to monitor and diagnose various medical conditions of the patient. Even though IMD"s are intelligent devices, in some cases they become more prone to attacks. Therefore a strong authentication mechanism has become mandatory for the IMD"s. Since IMD"s are ext… Show more
“…Several applications make use of IoT in data gathering process from smart environment like transports, homes, hospitals, cities and so on. Because of the growth in the IoT-based healthcare devices and sensors, lot of researchers are showing interest in that filed (Ganesan et al, 2015a). The rise of expensive medications and presence of various diseases globally, it importantly necessitates the revolution of healthcare from a hospital centric structure to patient-centric structure.…”
In the present days, e-health services offer various decision support systems in healthcare sector. These systems make use of internet of medical things (IoMT) devices and cloud platform to offer services to millions of people. In this paper, we develop an IoT with cloud-based brain tumour detection model using convolution neural network (CNN). Here, the input MRI brain images are captured by the use of medical equipments as well as IoT devices is used to transmit data to the cloud. In the cloud, the D-CNN model can be executed to identify the presence of disease and classify the brain tumour as malignant or benign. The presented D-CNN model is employed to a set of benchmark BRATS 2015 challenge dataset. The presented model attains maximum classifier performance with the sensitivity value of 97.17, specificity of 98.77 and accuracy of 98.07.
“…Several applications make use of IoT in data gathering process from smart environment like transports, homes, hospitals, cities and so on. Because of the growth in the IoT-based healthcare devices and sensors, lot of researchers are showing interest in that filed (Ganesan et al, 2015a). The rise of expensive medications and presence of various diseases globally, it importantly necessitates the revolution of healthcare from a hospital centric structure to patient-centric structure.…”
In the present days, e-health services offer various decision support systems in healthcare sector. These systems make use of internet of medical things (IoMT) devices and cloud platform to offer services to millions of people. In this paper, we develop an IoT with cloud-based brain tumour detection model using convolution neural network (CNN). Here, the input MRI brain images are captured by the use of medical equipments as well as IoT devices is used to transmit data to the cloud. In the cloud, the D-CNN model can be executed to identify the presence of disease and classify the brain tumour as malignant or benign. The presented D-CNN model is employed to a set of benchmark BRATS 2015 challenge dataset. The presented model attains maximum classifier performance with the sensitivity value of 97.17, specificity of 98.77 and accuracy of 98.07.
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