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Conventional implantable electronics based on von Neumann architectures encounter significant limitations in computing and processing vast biological information due to computational bottlenecks. The memristor with integrated memory-computing and low power consumption offer a promising solution to overcome the computational bottleneck and Moore's law limitations of traditional silicon-based implantable devices, making them the most promising candidates for next-generation implantable devices. In this work, a highly stable memristor with an Ag/BaTiO3/MnO2/FTO structure was fabricated, demonstrating retention characteristics exceeding 1200 cycles and endurance above 1000 s. The device successfully exhibited three-stage responses to biological signals after implantation in SD (Sprague-Dawley) rats. Importantly, the memristor perform remarkable reversibility, maintaining over 100 cycles of stable repetition even after extraction from the rat. This study provides a new perspective on the biomedical application of memristors, expanding the potential of implantable memristive devices in intelligent medical fields such as health monitoring and auxiliary diagnostics.

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The demand for an effective system that combines cutting-edge technologies with medical research to improve healthcare systems has increased with the development of medical technology. The most fundamental form of disease prevention is taking the right medication when needed. With the right care, many fatal diseases can be cured or prevented. Therefore, it is crucial to follow the doctor's recommended drug plan. Healthcare experts now have serious concerns about patients not being able to take their prescribed medications on time, particularly elderly patients. Due to age-related memory loss, people who have been given multiple prescriptions at once over an extended period of time are more likely to forget to take their medication on time or to take the wrong medication. Sometimes, a patient's inability to take the right medication at the right time might have a major impact on their health. Aside from being forgetful, patients, especially the elderly and illiterate, may not be able to read the name stated on medical containers, leading to the consumption of the wrong medication. These errors contribute to non-adherence to pharmaceuticals, which is detrimental to the patient's health. As a result, there is a significant problem that hinders the success of the treatment. The medication reminder system is intended for people who frequently take medications or vitamin supplements in order to handle this. In order to help an elderly person properly take their medication and help the patient have a healthy life, we have created a ground-breaking portable multifunctional medicine reminder kit with phone calls. Other intelligent characteristics of the smart medicine reminder include the capacity to show the time, date, and day in real time, the detection of smoke, the measurement of air humidity and temperature in the room, the measurement of heartbeats per second, the patient's body temperature, and the oxygen saturation level.

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BACKGROUNDS: Healthcare is a social and economic challenge in many countries, exacerbated by today's increasing demand. Many studies demonstrate that hospitals that move towards smartness, and some of their processes are smart, can provide more appropriate treatments and deal with problems more flexibly. It is axiomatic that implementing smart hospitals and healthcare tools requires a clear objective. However, the concept of a smart hospital lacks a comprehensive and broadly accepted definition, leading to varied interpretations and misconceptions. Many developments touted as 'smart' merely digitize existing hospital environments without truly embracing the full potential of smart technology. Furthermore, research studies have neglected to consider industrial perspectives, which will soon cause a gap between industry and academics in this concept. OBJECTIVES: This research aims to explore the attributes of a smart hospital and use them to propose a definition for it, considering both scholarly and industrial viewpoints. METHOD AND RESULTS: The PRISMA method is employed to select academic and practical papers providing definitions and insights into smart hospitals or healthcare. 17 studies are analyzed, and a total, 83 characteristics are identified to describe the smart hospital. These features are categorized into three primary categories: "technologies", "services", and "goals". The most important features are determined by analyzing the frequencies of these characteristics across all the studies. In the results section, these data are presented in graphical form, highlighting both academic and industrial perspectives separately, as well as a combined analysis. Furthermore, an attempt is made to uncover trends in smart hospitals from 2015 to 2023. CONCLUSION: A comprehensive definition of the smart hospital, encompassing both academic and industrial perspectives, is proposed using the investigated characteristics. This study also presents research opportunities and discusses the existing gap between academia and industry concerning smart hospitals.

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Objective To design an intelligent surgery management system for closed-loop management of the entire surgical process.Methods An intelligent surgery management system was developed with digital twin technology,Microsoft Visual Studio 12.0 development toolset and C# language,which realized multi-modal data acquisition with IoT devices such as radio frequency identification(RFID)bracelets,mobile terminals and positioning base stations and real-time data mirroring and gathering by change data capture(CDC)technology.There were four functional modules included in the system developed,including the modules for IoT device management,transfer process recording,intelligent management command chamber and surgical progress reminder.Results The system developed could provide real-time feedback on the operation status of all aspects of surgery,shorten the lengths of preoperative positioning and surgical reception and improve the satisfaction of both doctors and patients.Conclusion The system developed achieves closed-loop management and complete data traceability of the entire surgical process,helping to form an efficient and safe surgical operation management system.[Chinese Medical Equipment Journal,2024,45(1):42-46]

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Recently, in order to comprehensively promote the development of medical institutions and solve the nationwide problems in the healthcare fields, the government of China developed an innovative national policy of "Trinity" smart hospital construction, which includes "smart medicine," "smart services," and "smart management". The prototype of the evaluation system has been established, and a large number of construction achievements have emerged in many hospitals. In this article, the summary of this field was performed to provide a reference for medical workers, managers of hospitals, and policymakers.

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The development of information technology has had a significant impact on various areas of human activity, including medicine. It has led to the emergence of the phenomenon of Industry 4.0, which, in turn, led to the development of the concept of Medicine 4.0. Medicine 4.0, or smart medicine, can be considered as a structural association of such areas as AI-based medicine, telemedicine, and precision medicine. Each of these areas has its own characteristic data, along with the specifics of their processing and analysis. Nevertheless, at present, all these types of data must be processed simultaneously, in order to provide the most complete picture of the health of each individual patient. In this paper, after a brief analysis of the topic of medical data, a new classification method is proposed that allows the processing of the maximum number of data types. The specificity of this method is its use of a fuzzy classifier. The effectiveness of this method is confirmed by an analysis of the results from the classification of various types of data for medical applications and health problems. In this paper, as an illustration of the proposed method, a fuzzy decision tree has been used as the fuzzy classifier. The accuracy of the classification in terms of the proposed method, based on a fuzzy classifier, gives the best performance in comparison with crisp classifiers.

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Ionic skins are developed to mimic the mechanical properties and functions of natural skins. They have demonstrated substantial advantages to serve as the crucial interface to bridge the gap between humans and machines. The first-generation ionic skin is a stretchable capacitor comprising hydrogels as the ionic conductors and elastomers as the dielectrics, and realizes pressure and strain sensing through the measurement of the capacitance. Subsequent advances have been made to improve the mechanical properties of ionic skins and import diverse functions. For example, ultrahigh stretchability, strong interfacial adhesion, self-healing, moisturizing ability, and various sensing capabilities have been achieved separately or simultaneously. Most ionic skins are attached to natural skins to monitor bio-electrical signals continuously. Ionic skins have also been found with significant potential to serve as a smart drug-containing reservoir, which can release drugs spatially, temporally, and in a controllable way. Herein, this review focuses on the design and fabrication of ionic skins, and their applications related to smart medicine. Moreover, challenges and opportunities are also discussed. It is hoped that the development of bio-inspired ionic skins will provide a paradigm shift for self-diagnosis and healthcare.

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People have traditionally associated being 'not ill' with being 'healthy'. This concept has changed due to the improvement of Taiwan's population structure, advances in medical care, and better education. The word 'health' is defined by the World Health Organization as a state of complete physical, mental, and social well-being, and not merely the absence of disease or infirmity. In the future, people in Taiwan must address the challenges of population aging and create a society oriented to the long-term care needs of its citizens. People have different healthcare requirements during the respective stages of healthy, sub-healthy, and disability. Advancing technology has allowed the creation of many healthcare applications such as "health big data" that incorporate Internet of things (IoT) capabilities. Applying artificial intelligence opens many new possibilities and solutions. This article was written to introduce the application of big data techniques in smart healthcare that are appropriate to the three stages of healthy, sub-healthy, and disability.

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Background: Latest advances in information and health technologies enabled dentistry to follow the paradigm shift occurring in medicine - the transition to so called smart medicine. Consequently, the aim of this paper is to assess how 'smart' is smart dentistry as of the end of 2018. Methods: We analysed the state of the art in smart dentistry, performing bibliometric mapping on a corpus of smart dentistry papers found in the Scopus bibliographical database. Results: The search resulted in a corpus of 3451 papers, revealing that smart dentistry research is following the progress in smart medicine; however, there are some gaps in some specific areas like gamification and use of holistic smart dentistry systems. Conclusions: Smart dentistry is smart; however, it must become smarter.

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Innovation and rapid technological development in Smart Medicine or Smart Healthcare impact profoundly on many aspects of healthcare. It is believed that Health Information Technology (HIT) has the potential to improve integration between care providers, reduce administrative costs and burdens, reduce medical errors, and improve care quality and patient outcomes. However, issues such as interoperability, compatibility, and integration are critical to effectively integrating hardware and software in order to fully realize the benefits of HIT. High-end medical devices and equipment, including medical carts / mobile computer carts and wireless physiological and biomedical monitoring devices, should also be integrated into the hospital information system. Furthermore, the Data, Information, Knowledge, and Wisdom Hierarchy (DIKW) has been gaining popularity in the development of Nursing Information Systems (NIS) since 2013. To create a DIKW-based information system, data must first be defined and analyzed and then transformed into meaningful information. Eventually, this information is transformed into an intelligent system. For example, if evidence-based nursing research results / findings are integrated into the NIS to guide clinical practice, patient outcomes, patient safety, and healthcare quality will be greatly enhanced.

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According to the personalized service needs of patients with hypertension,diabetes and other chronic diseases,the paper develops a family self-service health management system based on intelligent terminal devices,introduces the system architecture,functions of each terminal,data communication and other key technologies.This system is able to provide patients and family members with real-time and effective disease prevention knowledge and targeted online medical treatment.