A Smart Sensing Technologies-Based Intelligent Healthcare System for Diabetes Patients.

An Artificial Intelligence (AI)-enabled human-centered smart healthcare monitoring system can be useful in life saving, specifically for diabetes patients. Diabetes and heart patients need real-time and remote monitoring and recommendation-based medical assistance. Such human-centered smart healthcare systems can not only provide continuous medical assistance to diabetes patients but can also reduce overall medical expenses. In the last decade, machine learning has been successfully implemented to design more accurate and precise medical applications. In this paper, a smart sensing technologies-based architecture is proposed that uses AI and the Internet of Things (IoT) for continuous monitoring and health assistance for diabetes patients. The designed system senses various health parameters, such as blood pressure, blood oxygen, blood glucose (non-invasively), body temperature, and pulse rate, using a wrist band. We also designed a non-invasive blood sugar sensor using a near-infrared (NIR) sensor. The proposed system can predict the patient's health condition, which is evaluated by a set of machine learning algorithms with the support of a fuzzy logic decision-making system. The designed system was validated on a large data set of 50 diabetes patients. The results of the simulation manifest that the random forest classifier gives the highest accuracy in comparison to other machine learning algorithms. The system predicts the patient's condition accurately and sends it to the doctor's portal.

Analysis of gold nanospheres, nano ellipsoids, nanorods, and effect of core-shell structures for hyperthermia treatment.

Hyperthermia (HT) is a technique for treating malignancies by raising the temperature of the defected tissues. This technique has been used as a treatment to raise tumor area temperatures between 42 °C to 48 °C. Hyperthermia penetrates deeper malignant cells by heating the region of interest when magnetic nanoparticles (MNPs) are exposed to an externally induced magnetic field of the incident wave. In this work, numerical analysis was used to examine the temporal and spatial temperature distributions within a tumor. The temperature field was analyzed using the mass transfer and diffusion theories in the interstitial tissue. A bio-heating module in COMSOL Multi-Physics was used for different types of gold nanoparticles (AuNPs) including nanorods, nanospheres, and nano-ellipsoids with different shapes. The objective of this study is to analyze the use of AuNPs for hyperthermia. The results show that AuNPs achieve a maximum temperature for Au nanorods as compared to nano ellipsoids and nanospheres. The Au NPs achieve thermal equilibrium after 0.5 µs and are effective for hyperthermia treatment. The results describe the effect of nanoparticle shape and surface coating on thermal absorption around the nanoparticle in hyperthermia. The significance of Au NPs for hyperthermia is explained. It is expected that this study will be helpful in the future for hyperthermia treatment.