Artificial Intelligence for Mobile Health Data Analysis and Processing

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EFFECTIVENESS OF CHATBOT TO REDUCE THE RISK OF CORONARY HEART DISEASE WITH DOKTERKIT MOBILE APPLICATION

Background: An innovative approach in the form of a discussion platform designed to help users deal with health issues related to coronary artery disease. Chatbot platforms allow the collection of users' data, which is analyzed through natural language processing and behavioral analysis to provide each user with a customized solution based on their current situation. The data collected and analyzed is accessible. The platform is developed using chatbot technology. Users can interact with chatbots to generate personal chat data stored on the platform.Conflicting information and sensitivity to Coronary heart disease (CHD) issues hinder effective communication. Recent technological solutions to maintain weight loss are limited. A chatbot would be suitable to support weight loss as it requires no human intervention, is available 24 hours a day, and supports natural communication while maintaining anonymity. CHD is a non-communicable disease with increased mortality in both developed and developing countries. It is a major public health problem worldwide. There are many risk factors for coronary heart disease, divided into primary risk factors (age, gender, genetics) and secondary risk factors (hypertension, smoking, dyslipidemia, diabetes, obesity, physical inactivity), and other risk factors (stress, alcohol, diet, and nutrition).The health system needs an effective and low-cost way to provide optimal health outcomes. Conversational Artificial Intelligence (AI) capabilities in the form of a fully automated and self-contained text-based mobile tutoring service. CHD is a serious health problem worldwide with multiple and interrelated causes. At the same time, chatbots are becoming more popular for interacting with users in mobile health apps.Objective: Dokterkit mobile application (available on the Google Play Store) prevents lifestyle-related diseases that are a risk for CHD, which has been considered to be at risk for multiple coronary artery disease (CAD), with the overarching goal of gaining compassion through mobile health improvements Opportunities for the healthcare of the heart. The insights gained in this preview article are used to plan future healthcare systems and design a system embedded with artificial intelligence to advance healthcare, chronic disease prevention, and self-treatment.Results: The Role of Artificial Intelligence in preventing Coronary Heart Disease (CHD) is to routinely carry out health screenings, make users aware of exercising regularly, and maintain food intake by reducing foods that are high in calories and adding foods that are high in fiber.Conclusion: Using AI in healthcare is associated with preventing CHD, which alters healthy lifestyles. It can also encourage a change in attitude, a high level of user concern for health, and obtain complete health information. Research on artificial intelligence and its use in telemedicine needs to be continued, with clinical trials examining the impact on blood pressure, body mass index, smoking, diabetes mellitus, and user engagement and feedback

LITERATURE REVIEW: Effectiveness of Chatbot to Reduce the Risk of Coronary Heart Disease using Android-based application

Background: An innovative approach in the form of a discussion platform designed to help users deal with health issues related to coronary artery disease. Chatbot platforms allow the collection of users' data, which is analyzed through natural language processing and behavioral analysis, to provide each user with a customized solution based on their current situation. The data collected and analyzed is accessible. The platform is developed using chatbot technology. Users can interact with chatbots to generate personal chat data stored on the platform. Conflicting information and sensitivity to Coronary Heart Disease (CHD) issues hinder effective communication. Recent technological solutions to maintain weight loss are limited. A chatbot would be suitable to support weight loss as it requires no human intervention, is available 24 hours a day, and supports natural communication while maintaining anonymity. The health system needs an effective and low-cost way to provide optimal health outcomes using conversation-enabled Artificial Intelligence (AI). Humans can interact well with this AI in the form of a fully automated and self-contained text-based mobile tutoring service. CHD is a serious health problem worldwide with multiple and interrelated causes. At the same time, chatbots are becoming more popular for interacting with users in mobile health apps.Objective: We evaluated an Android application. Its main goal is to prevent lifestyle-related diseases that are a risk for CHD, which has been considered at risk for multiple coronary artery disease (CAD), with the overarching goal of gaining compassion through mobile health improvements. The insights gained in this preview article will be used to plan future health care systems and to design an AI capable of advanced healthcare, chronic disease prevention, and self-treatment.Results: The Role of Artificial Intelligence in preventing Coronary Heart Disease (CHD) is done through health screenings. The app warns the user to exercise regularly and maintain food intake by reducing foods high in calories and adding foods high in fiber. Conclusion: Usage of AI in healthcare is associated with CHD prevention, which alters healthy lifestyles. It can also encourage a change in attitude, a high level of user concern for health, and obtain complete health information. Research on artificial intelligence and its use in telemedicine needs to be continued, with clinical trials examining the impact on blood pressure, body mass index, smoking, diabetes mellitus, and user engagement and feedback

Artificial intelligence for optimizing benefits and minimizing risks of pharmacological therapies: challenges and opportunities

In recent years, there has been an exponential increase in the generation and accessibility of electronic healthcare data, often referred to as “real-world data”. The landscape of data sources has significantly expanded to encompass traditional databases and newer sources such as the social media, wearables, and mobile devices. Advances in information technology, along with the growth in computational power and the evolution of analytical methods relying on bioinformatic tools and/or artificial intelligence techniques, have enhanced the potential for utilizing this data to generate real-world evidence and improve clinical practice. Indeed, these innovative analytical approaches enable the screening and analysis of large amounts of data to rapidly generate evidence. As such numerous practical uses of artificial intelligence in medicine have been successfully investigated for image processing, disease diagnosis and prediction, as well as the management of pharmacological treatments, thus highlighting the need to educate health professionals on these emerging approaches. This narrative review provides an overview of the foremost opportunities and challenges presented by artificial intelligence in pharmacology, and specifically concerning the drug post-marketing safety evaluation

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications