ABSTRACT
Introduction: Humankind is passing through a period of significant instability and a worldwide health catastrophe that has never been seen before. COVID-19 spread over the world at an unprecedented rate. In this context, we undertook a rapid research project in the Sultanate of Oman. We developed ecovid19 application, an ontology-based clinical decision support system (CDSS) with teleconference capability for easy, fast diagnosis and treatment for primary health centers/Satellite Clinics of the Royal Oman Police (ROP) of Sultanate of Oman. Material and Methods: The domain knowledge and clinical guidelines are represented using ontology. Ontology is one of the most powerful methods for formally encoding medical knowledge. The primary data was from the ROP hospital's medical team, while the secondary data came from articles published in reputable journals. The application includes a COVID-19 Symptom checker for the public users with a text interface and an AI-based voice interface and is available in English and Arabic. Based on the given information, the symptom checker provides recommendations to the user. The suspected cases will be directed to the nearby clinic if the risk of infection is high. Based on the patient's current medical condition in the clinic, the CDSS will make suitable suggestions to triage staff, doctors, radiologists, and lab technicians on procedures and medicines. We used Teachable Machine to create a TensorFlow model for the analysis of X-rays. Our CDSS also has a WebRTC (Web Real-Time Communication system) based teleconferencing option for communicating with expert clinicians if the patient develops difficulties or if expert opinion is requested. Results: The ROP hospital's specialized doctors tested our CDSS, and the user interfaces were changed based on their suggestions and recommendations. The team put numerous types of test cases to assess the clinical efficacy. Precision, sensitivity (recall), specificity, and accuracy were adequate in predicting the various categories of patient instances. Conclusion: The proposed CDSS has the potential to significantly improve the quality of care provided to Oman's citizens. It can also be tailored to fit other terrifying pandemics. © 2022, Published by Frontiers in Health Informatics.
ABSTRACT
The COVID-19 pandemic has disrupted daily lives and affected the entire healthcare system, including dental treatment. Efforts have been taken to formulate ways to counter the pandemic. Dental practices have adopted modifications of dental protocols with the incorporation of preventive measures. The aim of this survey was to study the patient outlook towards dental treatment and the awareness of patients about the preventive measures provided by their dentists in the post-Covid era. Hence a cross-sectional study was conducted on patients wanting to undergo dental treatments in the US, UK and India with a total of 121 participants per country during post covid pandemic. The study was conducted using a questionnaire prepared by the researcher, which consisted of 22 questions. The results showed that pain was the main reason for dental visits in all three countries. In the US and UK, a large percentage of people preferred video and teleconsulting even in the post-covid period, while in India, the majority preferred personal dental visits. The trend of avoiding dental treatment was widespread in India, displaying the level of ignorance and financial constraints among them. It indicates the need for better awareness about the importance of oral health and the inclusion of dental insurance schemes.
ABSTRACT
Coronavirus is an authentic WHO-proclaimed pandemic disease. Qualified professionals and medical care organizations experienced significant conditions across the world. In addition, the governmental authority develops a significant technique to alleviate the disease, to lock the nations. In this article, we proposed the covid detection system among the people by using several sensors embedded in a device to detect the people's disease. This system uses the Lora module for communication for the doctor's unit. IoT-based health networks attempt to improve health services quality through real-time data collecting and analysis. However, there are significant disadvantages with standard IoT systems. For example, they cannot function efficiently in locations with poor or unstable Internet. The solution to the question of internet services is a feasible option with technology like LPWAN (Low Power Wider Network), such as full-scale order elements, viz. Lora. The monitoring system plays a crucial role in diagnostic procedures and treatment. © 2023 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
The continents have been overtaken by chaos and tragedy as COVID-19 performs its cosmic dance. In such a situation, life satisfaction indices could decline while mental stress is likely to rise. The stress and life satisfaction levels among diabetes patients were expressed using descriptive statistics. The association between perceived stress and life satisfaction was examined using the chi-square test. The number of diabetic patients at our institution who were willing to enroll was a total of 140. Participants in the research had an average age of 52.38 + 14.9 years. 46.4 percent of the study's participants were above the age of 55. There is an urgent need to introduce stress busters because half (50%) of the participants reported moderate to high levels of stress. Additionally, about 20% of the individuals reported having trouble with stress. Stress may negatively affect a diabetic patient's ability to control their blood sugar, thus therapies that reduce or manage stress may be crucial in preventing the development of major diabetes problems in the future. Keywords:.
ABSTRACT
Usage of Internet has increased enormously in this decade due to the pandemic began due to COVID19. Data in the form of Text, Image and Video are communicated across the world through mails, chat applications and meeting applications etc. Such third-party applications are vulnerable while sensitive information such as personal, financial, medical and military communications occurs. Visual Cryptography (VC) is an encryption scheme that protects data in the form of image. In source, VC encrypts the image by dividing into shares and distributes to the receiver side. At the destination, the shares are stacked together physically or digitally to reveal the original data. VC also uses cover images to enhance security. VC supports secret sharing of multiple images. In this research paper, a new Multiple grayscale Secret Image Sharing (MSIS) strategy is proposed for secure transmission of more than one grayscale secret image data to the destination. MSIS uses color cover images to enhance the security. It also minimizes the number of shares and cover images to reduce the complexity.
ABSTRACT
Protecting Personally identifiable information (PII) and Protected health Information (PHI) is always challenging in this digital era. An ongoing global pandemic of coronavirus disease 2019 called as coronavirus pandemic (COVID-19), has forced people towards digital transaction of data all over the world. Telemedicine allows health care service providers to evaluate, diagnose and treat patients at a distance using telecommunications tools and technology. Patients communicate the medical reports, medical images and related documents by email. Data that carries PHI information, is communicated via public networks in the form of image and are vulnerable. An effective encryption technique is always in need to transfer such information securely. Visual Secret Sharing (VSS) scheme is an efficient encryption scheme that decodes the image by dividing into number of shares. Individual shares do not reveal any secret and stacking of all shares can reveal the secret image. In this article, Semantic Visual Secret Sharing scheme (SVSS) is proposed, which can be applicable for both gray-scale and color images. In this SVSS, the secret color image I is converted into semantic image SI by reducing the pixel errors. This SI decreases the encoding complexity without affecting the quality. The proposed SVSS avoids pixel expansion issues faced by traditional VSS schemes. Also, the Peak Signal-to-Noise Ratio (PSNR) value of the reconstructed secret color image shows better quality of the reconstructed secret image. The pixel errors that get introduced during share generation phase is reduced. The experimental result shows the effectiveness of the proposed SVSS and ensures secure transmission.
ABSTRACT
COVID-19 pandemic has rapidly spread across the world since its arrival in December 2019 from Wuhan, China. This pandemic has disrupted the health of the citizens in such a way that the impact is enormous in terms of economy and social aspects. Education, employment, income, well-being of the humankind is affected very crucially by this corona virus. Nations world-wide are struggling to battle this emergency. Intensive studies are being carried out to control this pandemic by researchers all over the world. Medical science has advanced a lot with the application of computer assisted solutions in health care. Ontology based clinical decision support systems (CDSS) assist medical practitioners in the diagnosis and treatment of diseases. They are well known in data sharing, interoperability, knowledge reuse, and decision support. This research article presents the development of ontology for SARS-CoV-2 (COVID-19) to be used in a CDSS, which is proposed in the satellite clinics of Royal Oman Police (ROP), Sultanate of Oman. The key concepts and the concept relationships of COVID-19 is represented using an ontology. Semantic Web Rule Language (SWRL) is used to model the rules related to the initial diagnosis of the patient and Semantic Query Enhanced Web Rule Language (SQWRL) is used to retrieve the data stored in the ontology. The developed ontology successfully classified the patients into one of the different categories as non-suspected, suspected, probable, and confirmed. The reasoning time and the query execution time is found to be optimal. © 2020. All Rights Reserved.