ABSTRACT
This book comprehensively covers the topic of COVID-19 and other pandemics and epidemics data analytics using computational modelling. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. The new era of pandemics and epidemics bring tremendous opportunities and challenges due to the plentiful and easily available medical data allowing for further analysis. The aim of pandemics and epidemics research is to ensure high-quality, efficient healthcare, better treatment and quality of life by efficiently analyzing the abundant medical, and healthcare data including patient's data, electronic health records (EHRs) and lifestyle. In the past, it was a common requirement to have domain experts for developing models for biomedical or healthcare. However, recent advances in representation learning algorithms allow us to automatically learn the pattern and representation of the given data for the development of such models. Medical Image Mining, a novel research area (due to its large amount of medical images) are increasingly generated and stored digitally. These images are mainly in the form of: computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients' biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions related to health care. Image mining in medicine can help to uncover new relationships between data and reveal new and useful information that can be helpful for scientists and biomedical practitioners. Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis will play a vital role in improving human life in response to pandemics and epidemics. The state-of-the-art approaches for data mining-based medical and health related applications will be of great value to researchers and practitioners working in biomedical, health informatics, and artificial intelligence. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
ABSTRACT
Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain provides imperative research on the development of data fusion and analytics for healthcare and their implementation into current issues in a real-time environment. While highlighting IoT, bio-inspired computing, big data, and evolutionary programming, the book explores various concepts and theories of data fusion, IoT, and Big Data Analytics. It also investigates the challenges and methodologies required to integrate data from multiple heterogeneous sources, analytical platforms in healthcare sectors. This book is unique in the way that it provides useful insights into the implementation of a smart and intelligent healthcare system in a post-Covid-19 world using enabling technologies like Artificial Intelligence, Internet of Things, and blockchain in providing transparent, faster, secure and privacy preserved healthcare ecosystem for the masses. © 2023 Elsevier Inc. All rights reserved.
ABSTRACT
The furious disease named COVID-19 is an outbreak in the current scenario. To control the spreading of this disease, new models were developed which utilized established methodologies to analyze how different containment strategies will influence the spread of the virus. It presents a novel machine learning approach that can estimate any epidemiological model's parameters based on two types of information: either static or dynamic. It primarily utilizes the Graph model using deep learning approaches and Long-term memories (LSTMs) to obtain mobility data's spatial and temporal properties of SIR and SIRD models. It runs and simulates using data on the Italian COVID dynamics and compares the model predictions to previously observed epidemics. © 2022 Scrivener Publishing LLC.
ABSTRACT
Education is the backbone of mankind's progress. Every country wants their children to be exposed to early childhood education so that that they are not left out of the benefits of education. The early childhood education begins at home however once they are able to express themselves they need to have some formal education which will augment their cognitive as well as social interactions as well as the rest of the world outside their homes. Educational institutes play a great role here from early leaning methods as well as advanced schooling as they grow up. For all these they have to go out of the home and interact with other children, teachers with a face to face interaction with physical presence. This was a well-established model until year 2020. During COVID 19 pandemic the entire world experienced a challenge which was just against the 2 core concept of education, outing out of home and meets someone physically. Educational institutesall over the world had challengeslife was sandwiched between lockdowns and unlocks and this was a never before challenge for them. Numerous individuals were the victims of the deadly virus which made the entire world a complex place to live in.All these had a direct impact on the uncertainty aspect in individuals as well as with the educational institutes. While the entire world struggled to deal with the unseen, uncertain and undesired state of affairs, the resiliency in human beings and educational models started accepting the struggle by adapting to the change the situation demanded for. Soon this acceptance helped educational institutes to be more resilient, productive and demand driven to run the educational activities as usual adopting the un-usual ways of education through completely online mode of education. Eventually education institutes and children learnt in the hard way that the world we live in is actually a VUCA (Volatile, Uncertain, Complex, and Ambiguous) world and at the same time continue imparting education to the children by accepting all changing parameters so that the educational outcome is achieved with resilience among all uncertainties. This study analyses the demand and supply chain of online education for children and proposes a paradigm shift that is required for education for children in time to come.
ABSTRACT
Cerebral palsy is a non-progressive disorder, which arising in early stages of development of child. There are many etiology factors like antenatal, natal and postnatal factors responsible for causing cerebral palsy but exact cause is still unknown. Spasticity is the main feature of cerebral palsy(). Classification of CP is too broad on the basis of physiological and topographic etc. Symptoms of spastic cerebral palsy can be corelated with Jadhata in Ayurveda. In Jadata, there is tightness of muscles occurs. Improvement can be got in children with ayurvedic treatment. Aim- To improve the quality of life of child suffered from spastic CP. Place and duration of study- Study was done in Parul Ayurved Hospital, Vadodara, Gujarat. Method- In this case study, Samavardhan ghrita() orally, snehana() with bala taila() and svedan () with dashmmola kwath () was given to child for 31 days. Results- mild improvement in spasticity and achievement of milestones have observed. Patient got discharged from IPD of hospital due to COVID 19 pandemic. Conclusion- Hence, through Ayurveda treatment, improvement in symptoms of spastic cerebral palsy can achieve and quality of life of child can increase spontaneously.
ABSTRACT
Ever since the pandemic of Coronavirus disease (COVID-19) emerged in Wuhan, China, it has been recognized as a global threat and several studies have been carried out nationally and globally to predict the outbreak with varying levels of dependability and accuracy. Also, the mobility restrictions have had a widespread impact on people's behavior such as fear of using public transportation (traveling with unknown passengers in the closed area). Securing an appropriate level of safety during the pandemic situation is a highly problematic issue that resulted from the transportation sector which has been hit hard by COVID-19. This paper focuses on developing an intelligent computing model for forecasting the outbreak of COVID-19. The autoregressive integrated moving average (ARIMA) machine learning model is used to develop the best model for twenty-one worst-affected states of India and six worst-hit countries of the world including India. The best ARIMA models are used for predicting the daily-confirmed cases for 90 days future values of six worst-hit countries of the world and six high incidence states of India. The goodness-of-fit measures for the model achieved 85% MAPE for all the countries and all states of India. The above computational analysis will be able to throw some light on the planning and management of healthcare systems and infrastructure. © 2013 IEEE.
ABSTRACT
Background: The coronavirus disease 2019(COVID-19) is an acute respiratory disease caused by a novel coronavirus(SARS CoV-2). Clinically COVID-19 presented with respiratory illness and also death is a possible outcome. Hearing loss is an interesting clinical outcome associated with COVID-19 infections. Objective: This study is designed to analyze the incidence of hearing loss in COVID-19 patients after discharge from the COVID-19 hospital. Methods: Twenty-eight patients of COVID-19 discharged from COVID hospital presenting with hearing loss participated in this study. The age ranges from 16 years to 52 years. Patients those had hearing loss before admission to COVID hospital were excluded from this study. All these patients underwent pure tone audiometry, tympanometry and Otoacoustic emission study. Results: Out of 28 patients, 18 (64.28%) were male and 10 (35.71%) were female with male to female ratio of 1.8:1. The age ranges of the participants were 16 to 52 years. Twenty-two patients presented with unilateral hearing loss and six presented with bilateral hearing loss. Out of 28 patients, 24 (85.71%) were presented with sensorineural hearing loss (SNHL) and 4 (14.28%) presented with conductive hearing loss. Out of the 28 patient 21 patients (75%) presented with unilateral hearing loss whereas 17 (60.71%) showed sudden-onset hearing loss. Conclusion: Hearing loss in COVID-19 has not received much attention by the medical professionals.COVID-19 infection could have deleterious effects on the inner ear specifically on the hair cells of the cochlea despite patients are asymptomatic. The proper understanding of the mechanisms behind hearing loss in COVID-19 infections needs further research. © IJCRR.