Surveying Healthcare Facilities for Tourists in India

India is quickly becoming one of the most popular tourist destinations in the world. The rise of India as a tourist destination can be attributed to a number of factors. The growth of medical tourism in India is one of the reasons examined in this paper. Healthcare tourism is when people from all over the world fly to another country to receive medical, dental, and surgical treatment when exploring, vacationing, and completely immersing themselves in the attractions of the countries they are visiting. In the medical tourism industry, India is one of the most popular destinations. Medical tourism is experiencing rapid growth in India. Medical tourists cross foreign boundaries in search of medical care. Medical tourism has developed to become a multibillion-dollar industry. It is important to remember that the primary goal of medical tourists is to provide high-quality medical care at an affordable cost. When compared to other developing countries in the world, India has emerged as the most sought-after destination for medical tourists due to the availability of world-class doctors at affordable prices. In addition, India has a wide range of tourist destinations. It has tremendous potential for creating jobs and earning large sums of foreign currency. The paper ends with policy recommendations for advancing the rapidly growing medical tourism industry.

An Analysis of COVID-19 Cases in G20 Countries and History of Previous Pandemics

This research paper focusses on the recent impact of Covid-19 on the G20 countries on basis of the number of cases and the number of deaths in several aspects. This paper also provides a brief history of the previously occurred pandemics and epidemics. A statistical analysis was conducted for 19 countries of the G20 assembly and presented in the paper. This topic was chosen in interest of recent events of the Covid-19 pandemic and its extensive effect on the world at large. The dataset consisting of records from nineteen countries was chosen as a part of the analysis. Apart from being involved in the G20 summit, these countries are looked upon by other countries of the world due to their economic and overall development. Further, past history of some pandemics and epidemics were taken into study.

Surveying Healthcare Facilities for Tourists in India

India is quickly becoming one of the most popular tourist destinations in the world. The rise of India as a tourist destination can be attributed to a number of factors. The growth of medical tourism in India is one of the reasons examined in this paper. Healthcare tourism is when people from all over the world fly to another country to receive medical, dental, and surgical treatment when exploring, vacationing, and completely immersing themselves in the attractions of the countries they are visiting. In the medical tourism industry, India is one of the most popular destinations. Medical tourism is experiencing rapid growth in India. Medical tourists cross foreign boundaries in search of medical care. Medical tourism has developed to become a multibillion-dollar industry. It is important to remember that the primary goal of medical tourists is to provide high-quality medical care at an affordable cost. When compared to other developing countries in the world, India has emerged as the most sought-after destination for medical tourists due to the availability of world-class doctors at affordable prices. In addition, India has a wide range of tourist destinations. It has tremendous potential for creating jobs and earning large sums of foreign currency. The paper ends with policy recommendations for advancing the rapidly growing medical tourism industry.

An Analysis of COVID-19 Cases in G20 Countries and History of Previous Pandemics

This research paper focusses on the recent impact of Covid-19 on the G20 countries on basis of the number of cases and the number of deaths in several aspects. This paper also provides a brief history of the previously occurred pandemics and epidemics. A statistical analysis was conducted for 19 countries of the G20 assembly and presented in the paper. This topic was chosen in interest of recent events of the Covid-19 pandemic and its extensive effect on the world at large. The dataset consisting of records from nineteen countries was chosen as a part of the analysis. Apart from being involved in the G20 summit, these countries are looked upon by other countries of the world due to their economic and overall development. Further, past history of some pandemics and epidemics were taken into study

Application of Technologies Robotic Rehabilitation in Children with Upper Limb Injury

Robotic and advanced technology rehabilitation is useful for people with difficulties and deficits in arm and hand movements, walking problems and balance disorders. Robotic technologies are being introduced in the rehabilitation field to support the activity of specialists, doctors and physiotherapists; the future and the challenge of rehabilitation lies precisely in the development of robotics. Robot assists the therapist in administering the most appropriate motor therapy with precision and repeatability modulates the difficulty of the exercise. It allows repetitive task-oriented activities with augmentative feedback capable of inducing brain plasticity. It acquires quantitative information on movement and evaluates the services performed he first, “Arm and Hand”, is used to help the opening and closing movements of the hand. After entering it by hand and forearm, gently guides the patient's shoulder and elbow movements to reach and grasp objects. “Wrist”, on the other hand, interacts with the movements of the wrist and integrates functionally with the “Hand” module.

Application of Technologies Robotic Rehabilitation in Children with Upper Limb Injury

Robotic and advanced technology rehabilitation is useful for people with difficulties and deficits in arm and hand movements, walking problems and balance disorders. Robotic technologies are being introduced in the rehabilitation field to support the activity of specialists, doctors and physiotherapists; the future and the challenge of rehabilitation lies precisely in the development of robotics. Robot assists the therapist in administering the most appropriate motor therapy with precision and repeatability modulates the difficulty of the exercise. It allows repetitive task-oriented activities with augmentative feedback capable of inducing brain plasticity. It acquires quantitative information on movement and evaluates the services performed he first, “Arm and Hand”, is used to help the opening and closing movements of the hand. After entering it by hand and forearm, gently guides the patient’s shoulder and elbow movements to reach and grasp objects. “Wrist”, on the other hand, interacts with the movements of the wrist and integrates functionally with the “Hand” module.

Chronic Kidney Disease Prediction using Machine Learning Algorithms

Kidney diseases are increasing day by day among people. It is becoming a major health issue around the world. Not maintaining proper food habits and drinking less amount of water are one of the major reasons that contribute this condition. With this, it has become necessary to build up a system to foresee Chronic Kidney Diseases precisely. Here, we have proposed an approach for real time kidney disease prediction. Our aim is to find the best and efficient machine learning (ML) application that can effectively recognize and predict the condition of chronic kidney disease. We have used the data from UCI machine learning repository. In this work, five important machine learning classification techniques were considered for predicting chronic kidney disease which are KNN, Logistic Regression, Random Forest Classifier, SVM and Decision Tree Classifier. In this process, the data has been divided into two sections. In one section train dataset got trained and another section got evaluated by test dataset. The analysis results show that Decision Tree Classifier and Logistic Regression algorithms achieved highest performance than the other classifiers, obtaining the accuracy of 98.75% followed by random Forest, which stands at 97.5%.

Chronic Kidney Disease Prediction using Machine Learning Algorithms

Kidney diseases are increasing day by day among people. It is becoming a major health issue around the world. Not maintaining proper food habits and drinking less amount of water are one of the major reasons that contribute this condition. With this, it has become necessary to build up a system to foresee Chronic Kidney Diseases precisely. Here, we have proposed an approach for real time kidney disease prediction. Our aim is to find the best and efficient machine learning (ML) application that can effectively recognize and predict the condition of chronic kidney disease. We have used the data from UCI machine learning repository. In this work, five important machine learning classification techniques were considered for predicting chronic kidney disease which are KNN, Logistic Regression, Random Forest Classifier, SVM and Decision Tree Classifier. In this process, the data has been divided into two sections. In one section train dataset got trained and another section got evaluated by test dataset. The analysis results show that Decision Tree Classifier and Logistic Regression algorithms achieved highest performance than the other classifiers, obtaining the accuracy of 98.75% followed by random Forest, which stands at 97.5%.

Proposed a Framework for Depression Monitoring System by Detecting the Facial Expression using Soft Computing Algorithm

Healthcare Informatics plays a very important role for manipulating data. In the healthcare discoveries, pattern recognition is important for the prediction of depression, aggression, pain and severe disease diagnostics. In [16][5], the real innovation that has affected and organized human services is cloud computing, which empowers whenever anyplace access to the information put away in a cloud. The mobile devices are continuously observing patients that move around a networked healthcare environment. In traditional healthcare diagnostic system, we depend upon expensive tests and machineries which increase the expenditure of healthcare. It is dire need to reduce the aggregate cost of regular or usual diagnostics incorporates high cost of hospitalization. These expenses can be limited or disposed of with the assistance of remote patient monitoring gadget, a healthcare IoT product. Remote monitoring of person’s health gadget includes the observing of a person from an alternate area. This dispenses the requirement for driving to clinic and to being hospitalized for less severe circumstances. This research will explore the depression monitoring system by detecting the facial expression using suitable soft computing algorithm. We may use different algorithms such as CNN and Multilayer Perceptron to get the best result. On the basis of classification it detects the class of disease. For this purpose, the primary dataset from various facial expressions of a patient will be collected, filtered and apply to classification algorithm to train the model.