An Enhancement on Convolutional Artificial Intelligent Based Diagnosis for Skin Disease Using Nanotechnology Sensors.

Skin disease is the major health problem around the world. The diagnosis of skin disease remains a challenge to dermatologist profession particularly in the detection, evaluation, and management. Health data are very large and complex due to this processing of data using traditional data processing techniques is very difficult.

A Smart Solution for Cancer Patient Monitoring Based on Internet of Medical Things Using Machine Learning Approach.

The Internet of Medical Things (IoMT) is a huge, exciting new phenomenon that is changing the world of technology and innovating various industries, including healthcare. It has specific applications and changes in the medical world based on what can be done for clinical workflow models. The first and most fundamental thing that IoMT does in healthcare is to bring a flood of new data into medical processes.

Implementation of Artificial Neural Network to Predict Diabetes with High-Quality Health System.

Patients with diabetes who are closely monitored have a higher overall quality of life than those who are not. Costs associated with healthcare can be decreased by utilising the Internet of Things (IoT), thanks to technological advancements. To satisfy the expectations of e-health applications, it is required for the development of the intelligent systems as well as increases the number of applications that are connected to the network.

An Artificial Intelligence-Based Reactive Health Care System for Emotion Detections.

In the past few years, remote monitoring technologies have grown increasingly important in the delivery of healthcare. According to healthcare professionals, a variety of factors influence the public perception of connected healthcare systems in a variety of ways. First and foremost, wearable technology in healthcare must establish better bonds with the individuals who will be using them.

Segmentation of Optic Disc and Cup Using Modified Recurrent Neural Network.

Glaucoma is one of the leading factors of vision loss, where the people tends to lose their vision quickly. The examination of cup-to-disc ratio is considered essential in diagnosing glaucoma. It is hence regarded that the segmentation of optic disc and cup is useful in finding the ratio.

Healthcare Biclustering-Based Prediction on Gene Expression Dataset.

In this paper, we develop a healthcare biclustering model in the field of healthcare to reduce the inconveniences linked to the data clustering on gene expression. The present study uses two separate healthcare biclustering approaches to identify specific gene activity in certain environments and remove the duplication of broad gene information components. Moreover, because of its adequacy in the problem where populations of potential solutions allow exploration of a greater portion of the research area, machine learning or heuristic algorithm has become extensively used for healthcare biclustering in the field of healthcare.

Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data.

Remote health monitoring can help prevent disease at the earlier stages. The Internet of Things (IoT) concepts have recently advanced, enabling omnipresent monitoring. Easily accessible biomarkers for neurodegenerative disorders, namely, Alzheimer's disease (AD) are needed urgently to assist the diagnoses at its early stages.

Application of Internet of Things on the Healthcare Field Using Convolutional Neural Network Processing.

Population at risk can benefit greatly from remote health monitoring because it allows for early detection and treatment. Because of recent advances in Internet-of-Things (IoT) paradigms, such monitoring systems are now available everywhere. Due to the essential nature of the patients being monitored, these systems demand a high level of quality in aspects such as availability and accuracy.

Design of Resources Allocation in 6G Cybertwin Technology Using the Fuzzy Neuro Model in Healthcare Systems.

In 6G edge communication networks, the machine learning models play a major role in enabling intelligent decision-making in case of optimal resource allocation in case of the healthcare system. However, it causes a bottleneck, in the form of sophisticated memory calculations, between the hidden layers and the cost of communication between the edge devices/edge nodes and the cloud centres, while transmitting the data from the healthcare management system to the cloud centre via edge nodes. In order to reduce these hurdles, it is important to share workloads to further eliminate the problems related to complicated memory calculations and transmission costs.

Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications.

Authentication is a suitable form of restricting the network from different types of attacks, especially in case of fifth-generation telecommunication networks, especially in healthcare applications. The handover and authentication mechanism are one such type that enables mitigation of attacks in health-related services. In this paper, we model an evolutionary model that uses a fuzzy evolutionary model in maintaining the handover and key management to improve the performance of authentication in nanocore technology-based 5G networks.

Extraction of the molecular level biomedical event trigger based on gene ontology using radial belief neural network techniques.

Detection of molecular level biomedical event extraction plays a vital role in creating and visualizing the applications related to natural language processing. Cystic Fibrosis is an inherited genetic and debilitating pathology involving the respiratory and digestive systems. The excessive production of thick sticky mucus on the outside of the cells is the main consequence of such disease.

Synthesis, DNA binding and in-vitro cytotoxicity studies on novel bis-pyrazoles.

A new series of bis-pyrazoles 6a-t were synthesized from 3,5-dimethyl pyrazole using sequential approach. All these compounds were characterized by IR, H NMR, C NMR and mass spectral data. The interaction of newly synthesized bis-pyrazoles with DNA was investigated through molecular docking and absorption spectroscopic technique.

An efficient synthesis and biological screening of benzofuran and benzo[d]isothiazole derivatives for Mycobacterium tuberculosis DNA GyrB inhibition.

A series of twenty eight molecules of ethyl 5-(piperazin-1-yl)benzofuran-2-carboxylate and 3-(piperazin-1-yl)benzo[d]isothiazole were designed by molecular hybridization of thiazole aminopiperidine core and carbamide side chain in eight steps and were screened for their in vitro Mycobacterium smegmatis (MS) GyrB ATPase assay, Mycobacterium tuberculosis (MTB) DNA gyrase super coiling assay, antitubercular activity, cytotoxicity and protein-inhibitor interaction assay through differential scanning fluorimetry. Also the orientation and the ligand-protein interactions of the top hit molecules with MS DNA gyrase B subunit active site were investigated applying extra precision mode (XP) of Glide. Among the compounds studied, 4-(benzo[d]isothiazol-3-yl)-N-(4-chlorophenyl)piperazine-1-carboxamide (26) was found to be the most promising inhibitor with an MS GyrB IC50 of 1.

Studies on the shelf-life enhancement of potato stuffed parotha using thermal processing.

Convenient, ready-to consume thermally processed potato stuffed parothas retaining their natural sensory attributes have been developed. Response Surface Methodology was used to optimize the Stuffing: dough ratio along with other ingredients. Optimized Stuffed parothas were packed in indigenously developed retortable pouches and processed in a steam-air retort.

Design, synthesis, biological evaluation of substituted benzofurans as DNA gyraseB inhibitors of Mycobacterium tuberculosis.

DNA gyrase of Mycobacterium tuberculosis (MTB) is a type II topoisomerase and is a well-established and validated target for the development of novel therapeutics. By adapting the medium throughput screening approach, we present the discovery and optimization of ethyl 5-(piperazin-1-yl) benzofuran-2-carboxylate series of mycobacterial DNA gyraseB inhibitors, selected from Birla Institute of Technology and Science (BITS) database chemical library of about 3000 molecules. These compounds were tested for their biological activity; the compound 22 emerged as the most active potent lead with an IC50 of 3.

Development of shelf stable protein rich composite cereal bar.

Protein rich composite cereal bar based on cereal ingredients was prepared using semi automatic tablet making machine, packed in poly propylene (PP), paper aluminium foil polyethylene (PFP), metallised polyester (MP) followed by vacuum packing in metallized polyester films. Proximate composition, mineral contents as well as changes in peroxide value (PV), free fatty acid value (FFA), thiobarbituric acid value (TBA), browning, fatty acid profile, vitamins, effect of water activity on lipid peroxidation, fortification with vitamins and minerals, microbiological as well as sensory parameters during storage under ambient (15-34°C) and 37°C temperature conditions were studied. Composite cereal bar remained shelf stable for 3 months in PP and 6 months in PFP, MP and MP plus vacuum packing under ambient and 37°C temperature conditions.

Quality of fried broiler chicken leg muscles stored at different temperatures.

Chicken leg pieces (60 g each). with optimized quantity of additives were fried in hydrogenated vegetable oil at 180°C for 8 min. The fried product was packed in paper-foil-polyethylene pouches (PFP) and stored under ambient (20 ± 5°C, 65-80% RH), refrigerator (5°C, 80% RH) and deep freezer (-18°C, 85-90% RH) conditions.

Increased collagen and glycoprotein contents of the denervated cremaster muscle of the bonnet monkey, Macaca radiata.

Denervation of genitofemoralis in the bonnet monkey for 60 days resulted in a significant increase in neutral salt-soluble, alkali-soluble and insoluble collagens as well as glycoproteins. The hydroxyproline content of the salt-soluble and insoluble collagens in the muscle increased on denervation. These changes are discussed to imply the impairment of the action of specific structural genes.