Security and Privacy of Cloud- and IoT-Based Medical Image Diagnosis Using Fuzzy Convolutional Neural Network.

In recent times, security in cloud computing has become a significant part in healthcare services specifically in medical data storage and disease prediction. A large volume of data are produced in the healthcare environment day by day due to the development in the medical devices. Thus, cloud computing technology is utilised for storing, processing, and handling these large volumes of data in a highly secured manner from various attacks.

A ruthenium(IV) disulfide based non-enzymatic sensor for selective and sensitive amperometric determination of dopamine.

An electrochemical dopamine (DA) sensor has been fabricated by modifying a glassy carbon electrode (GCE) with ruthenium disulfide (RuS) nanoparticles (NPs). FESEM and TEM micrographs show the NPs to have an average size of ~45 nm. XRD, Raman and EDS, in turn, confirm the successful formation of cubic phased RuS NPs.

Quantitative thermal sensory testing in patients with amyotrophic lateral sclerosis using reaction time exclusive method of levels (MLE).

Objectives: Quantitative thermal sensory testing (QST) systems are used for the noninvasive quantification of sensory nerve function including the small myelinated and unmyelinated fibres which is not provided by classical sensory nerve conduction studies. Although Amyotrophic Lateral Sclerosis (ALS) is a pure motor disorder, nevetheless involvement of the sensory fires has been reported occasionally by various techniques. In the present study Reaction Time Exclusive Method of Levels (MLE) was used to detect somatic small fibre involvement in ALS patients with no sensory abnomalities on routine NCS.