Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Malfunctions in the immune system cause multiple sclerosis (MS), which initiates mild to severe nerve damage. MS will disturb the signal communication between the brain and other body parts, and early diagnosis will help reduce the harshness of MS in humankind. Magnetic resonance imaging (MRI) supported MS detection is a standard clinical procedure in which the bio-image recorded with a chosen modality is considered to assess the severity of the disease.

Three-Dimensional Semantic Segmentation of Diabetic Retinopathy Lesions and Grading Using Transfer Learning.

Diabetic retinopathy (DR) is a drastic disease. DR embarks on vision impairment when it is left undetected. In this article, learning-based techniques are presented for the segmentation and classification of DR lesions.

Recognition of Knee Osteoarthritis (KOA) Using YOLOv2 and Classification Based on Convolutional Neural Network.

Knee osteoarthritis (KOA) is one of the deadliest forms of arthritis. If not treated at an early stage, it may lead to knee replacement. That is why early diagnosis of KOA is necessary for better treatment.

A novel oppositional binary crow search algorithm with optimal machine learning based postpartum hemorrhage prediction model.

Postpartum hemorrhage (PPH) is an obstetric emergency instigated by excessive blood loss which occurs frequently after the delivery. The PPH can result in volume depletion, hypovolemic shock, and anemia. This is particular condition is considered a major cause of maternal deaths around the globe.

Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Multiple sclerosis (MS) is an autoimmune disease that causes mild to severe issues in the central nervous system (CNS). Early detection and treatment are necessary to reduce the harshness of the disease in individuals. The proposed work aims to implement a convolutional neural network (CNN) segmentation scheme to extract the MS lesion in a 2D brain MRI slice.

An Integrated Algorithmic MADM Approach for Heart Diseases' Diagnosis Based on Neutrosophic Hypersoft Set with Possibility Degree-Based Setting.

The possibility neutrosophic hypersoft set (pNHs-set) is a generalized version of the possibility neutrosophic soft set (pNs-set). It tackles the limitations of the pNs-set regarding the use of the multi-argument approximate function. This function maps sub-parametric tuples to a power set of the universe.

Optimal recycle price game theory model for second-hand mobile phone recycling.

Human societies develop rapidly through the advancement of technology; however, with these advancements, many problems are emerging. The topic chosen for this study surrounds the e-waste, which has become a major problem around the world. Second-hand and unused mobile phones are a big part of globally generated e-waste.

Fuzzy-based adaptive learning network using search and rescue optimization for e-waste management model: case study.

In recent days, the expansion of e-waste disposal should be increased due to environmental hazards, contamination of groundwater, an unconcerned consequence on marine life, human health, and decrease in the fertility of the soil. The majority of the developing countries are facing massive issues in implementing sustainable e-waste management schemes. The unofficial e-waste management schemes in the region of Chandigarh, India, have become a serious dispute for the government and several stakeholders due to human health and environmental effects.

Internet of things-assisted advanced dynamic information processing system for physical education system.

Background: In recent years the Internet of Things (IoT) has become a popular technological culture in the physical education system. Though several technologies have grown in the physical education system domain, IoT plays a significant role due to its optimized health information processing framework for students during workouts.

Objective: In this paper, an advanced dynamic information processing system (ADIPS) has been proposed with IoT assistance to explore the traditional design architecture for physical activity tracking.

Behavior-based swarm model using fuzzy controller for route planning and E-waste collection.

Nowadays, because of the increase in consumption of electronic equipment and its resource utilization, household e-waste has been generated gradually. The increase in e-waste generation brought environmental burdens as well as a health risk in several nations. The disposal of e-waste in landfills is not recommended due to some poisonous and contaminated chemicals.

Design of a workstation based on a human-interfacing robot for occupational health and safety.

Background: Robots communicate with the physical world program with the mechanic's simulations. They recommend that people-to-people robotics will prepare for cognitive models. Presently, there is a considerable concern for greater flexibility and efficiency in the scope of human-robot interfacing collaboration across hospitals.