Medical Smart Research Articles

An SDN-AI-Based Approach for Detecting Anomalies in Imbalance Data Within a Network of Smart Medical Devices

An SDN-AI-Based Approach for Detecting Anomalies in Imbalance Data Within a Network of Smart Medical Devices

SMART Medical Review: Acute Pancreatitis Assessment and Management in the First 24 Hours

Acute pancreatitis (AP) is an inflammatory reaction of the pancreas caused by inappropriate trypsin activation and an injury / innate inflammatory response. The many etiologies and potentially life-threatening consequences of AP require that clinicians initiate prompt and individualized treatment upon diagnosis. Application of new advances in the management of AP are required at the point of care. To facilitate care, a group of clinical experts have developed a set of recommendations for the evaluation and management of AP during the first 24 hours based on current evidence and evolving concepts. Ten areas of care are addressed where expert recommendations may be useful: (1) physical examination, (2) laboratory tests, (3) diagnosis, (4) early treatment, (5) severity determination, (6) etiology-based management, (7) typical orders sets, (8) determining of appropriate level of care, (9) quality of care, and (10) quality improvement recommendations. Conclusion: These recommendations should become available as clinical decision support tools that are accessible at the point of care, in real time.

Sustainable Innovative Design of Elderly-Friendly Smart Medical Products: An Integrated Model

Under the promotion of combined medical and elderly care (CMEC) policies, the market demand for elder-friendly smart medical products as convenient intelligent healthcare devices is growing. However, most studies on elderly-friendly smart medical products focus on functional enhancement and cost control, and there is a lack of research on the sustainable innovative design of elder-friendly smart medical products from the perspective of elderly emotional needs. Therefore, this paper proposes an integrated framework based on the fuzzy Kano model, Kansei engineering, and theory of inventive problem solving (TRIZ) for mapping the complex and dynamic emotional needs of the elderly to product design parameters to produce innovative solutions, ensuring the sustainability of the design process and the innovativeness of the design solutions of elder-friendly smart medical devices. We verified the effectiveness and applicability of this integrated framework through a case study involving sustainable innovation design of a smart blood pressure device. The results of this study are of considerable theoretical and practical significance for promoting the development of the market for elder-friendly smart medical products under the policy of CMEC, meeting the needs of the elderly for healthcare devices and improving their quality of life.

User Engagement with the User Manuals of Smart Medical Wearable Technologies and Relevant Questions of User Behavior.

In this paper, engagement with smart medical wearables and with their user manuals, as well as related user behavior are studied. A research questionnaire containing 15 single-choice questions was completed by 1381 test participants to address relevant topics of the investigated area, including trust in measured medical data, device calibration, technical terminologies and function discovery in the documentation, information sources beyond the documentation, and wearing such devices to bed. The questionnaire particularly focused on device functionalities and characteristics that initially led to the purchase of the smart medical wearable.

Correlation between psychological traits and the use of smart medical services in young and middle-aged adults: An observational study

BACKGROUND Psychological problems affect economic development. However, there is a huge gap between mental health service resources and mental health service needs. Existing mental health service technology and platforms cannot meet all the diverse mental health needs of people. Smart medicine is a new medical system based online that can effectively improve the quality and efficiency of medical services and make mental health services accessible. AIM To explore the level of intelligent medical use among young and middle-aged people and its correlation with psychological factors. METHODS Convenience sampling was used to select 200 young and middle-aged patients with medical experience at the Third People's Hospital of Chengdu between January 2022 and January 2023 as the research subjects. The general condition Questionnaire, Eysenck Personality Questionnaire, Symptom Checklist-90, General Health Questionnaire, and Smart Medical Service Use Intention Questionnaire were used to collect data. Pearson’s correlation was used to analyze the correlation between the participants’ willingness to use smart medical services and their personality characteristics, psychological symptoms, and mental health. RESULTS The results revealed that the mental health of young and middle-aged people was poor, and some had psychological problems such as anxiety, depression, and physical discomfort. Familiarity, acceptance, and usage of smart healthcare in this population are at a medium level, and these levels correlate with psychological characteristics. Acceptance was positively correlated with E, and negatively correlated with P, anxiety, fear, anxiety/insomnia, and social dysfunction. The degree of use was negatively correlated with P, obsessive-compulsive symptoms, depression, anxiety, hostility, paranoia, and somatic symptoms. CONCLUSION The familiarity, acceptance, and usage of smart medical services among the middle-aged and young groups are related to various psychological characteristics.

Rapid Review of Generative AI in Smart Medical Applications

With the continuous advancement of technology, artificial intelligence has significantly impacted various fields, particularly healthcare. Generative models, a key AI technology, have revolutionized medical image generation, data analysis, and diagnosis. This article explores their application in intelligent medical devices. Generative models enhance diagnostic speed and accuracy, improving medical service quality and efficiency while reducing equipment costs. These models show great promise in medical image generation, data analysis, and diagnosis. Additionally, integrating generative models with IoT technology facilitates real-time data analysis and predictions, offering smarter healthcare services and aiding in telemedicine. Challenges include computational demands, ethical concerns, and scenario-specific limitations.

Smart Medical Evacuation Support System for the Military.

Medical support in crisis situations is a major challenge. Efficient implementation of the medical evacuation process especially in operations with limited human resources that may occur during armed conflicts can limit the loss of these resources. Proper evacuation of wounded soldiers from the battlefield can increase the chances of their survival and rapid return to further military operations. This paper presents the technical details of the decision support system for medical evacuation to support this process. The basis for the functioning of this system is the continuous measurement of vital signs of soldiers via a specialized measurement module with a set of medical sensors. Vital signs values are then transmitted via the communication module to the analysis and inference module, which automatically determines the color of medical triage and the soldier's chance of survival. This paper presents the results of tests of our system to validate it, which were carried out using test vectors of soldiers' vital signs, as well as the results of the system's performance on a group of volunteers who performed typical activities of tactical operations. The results of this study showed the usefulness of the developed system for supporting military medical services in military operations.

Survey on A Smart Medical System on Drug Analysis using ML Algorithms

Online health communities continue to offer huge variety of medical information useful for medical practitioners, system administrators and patients alike. In this system we collect real time health posts from reputed websites, where patients express their views, including their experiences and side-effects on drugs used by them. We propose to perform Summarization of user posts per drug, and come out with useful conclusions for medical fraternity as well as patient community at a glance. Further, we propose to classify the users based on their ‘emotional state of mind’. Also, we shall perform knowledge discovery from user posts, whereby useful ‘patterns’ about the triad ‘drugs-symptoms-medicine’ is done by Association Rule Mining. Association rule mining is a popular and widely-known machine learning task. It is used to find out interesting relations between variables in large database. Rules generated by association have two disjoint set of items having form LHS (Left Hand Side) => RHS (Right Hand Side). The rule says that RHS is likely to occur whenever the LHS set occurs.

Smart Medical Health Prediction System Application Using Data Mining

Abstract: This project can benefit from the use of data mining techniques in a variety of fields, including science, medicine, and education. Because of laws and computer accessibility, a lot of data is now available in the medical and health care sectors. It is no longer necessary to handle such a large amount of data at once because of the significant advancements in computer technology made by modern technology. Evaluating data mining methods for clinical and healthcare applications is one of the paper's main goals, which aims to facilitate informed decision-making. In the world of computers, this well-known and potent technology is highly sought after. It is a branch of computer science that creates new research and findings from data that is already available in various databases. It extracts new patterns from massive data sets and the knowledge associated with these patterns by utilizing Artificial Intelligence, machine learning, and database management techniques. This method can be used to extract data automatically or semi-automatically. Clustering, forecasting, path analysis, and predictive analysis are some of the various parameters used in data mining.

Smart Medical Application of Deep Learning (MUNet) for Detection of COVID-19 from Chest Images

Fighting the outbreak of COVID-19 is now one of humanity's most critical matters. Rapid detection and isolation of infected people are crucial for decelerating the disease's spread. Due to the pandemic, the conventional technique for COVID-19 detection, reverse transcription-polymerase chain reaction, is time-consuming and in small abundance. Therefore, studies have been searching for alternate methods for detecting COVID-19, and thus applying deep learning methods to patients' chest images has been rendering impressive performance. The primary objective of this study is to suggest a technique for COVID-19 detection in chest images that is both efficient and reliable. We propose a deep learning method for COVID-19 classification based on a modified UNet called (Covid-MUNet). The Covid-MUNet model is trained using publicly available datasets, including chest X-ray images for multi-class classification (3-class and 4-classes) and CT scans images for binary/multi-class classification (2-classes and 3-classes). Using chest images, the Covid-MUNet is a successful methodology that helps physicians rapidly identify patients with COVID-19, thereby delaying the fast spread of COVID-19. The proposed model achieved an overall accuracy of 97.44% in classifying three categories (COVID-19, Normal, and Pneumonia) and an accuracy of 96.57% in classifying two categories (COVID-19 and Normal).

Smart Medical Appointment Scheduling: Optimization, Machine Learning, and Overbooking to Enhance Resource Utilization

Smart Medical Appointment Scheduling: Optimization, Machine Learning, and Overbooking to Enhance Resource Utilization

Research on Digital Transformation of Medical Insurance—Taking Zhejiang Smart Medical Insurance as an Example

Research on Digital Transformation of Medical Insurance—Taking Zhejiang Smart Medical Insurance as an Example

Conceptual Design and Implementation of FIDO2 compatible Smart Medical Card for Healthcare Information System

Conceptual Design and Implementation of FIDO2 compatible Smart Medical Card for Healthcare Information System

Smart Medical Rescue via Efficient Vehicle Road Cooperation: AIoT Framework

Smart Medical Rescue via Efficient Vehicle Road Cooperation: AIoT Framework

Smart Medical Systems Based IoT: Exploring the Relationship Between Essential Algorithms and Service Orientation

This study examines the most recent research publications that focus on the Internet of Things (IoT) in medical systems including health monitoring, fitness programs, etc., as a consequence of the IoT's explosive growth in these areas. The monitoring efficiency of IoT-based healthcare systems has been the subject of much study. In this paper, we go into the architecture of the Internet of Things, namely the cloud-integrated systems. As accuracy and power consumption are major issues in the Internet of Things, studies that aim to enhance the efficiency of healthcare systems that rely on the IoT are highlighted. This research also provides a thorough examination of the strategies used for data management in IoT-based healthcare systems that make use of cloud services. The benefits and drawbacks of the IoT-based healthcare system are discussed, as well as its performance. Studies often have a high percentage of success in identifying multiple symptoms and making illness predictions. When it comes to keeping tabs on the health of the elderly population, the Internet of Things-based healthcare system developed specifically for them is an effective answer. Existing systems have many drawbacks, including high power consumption, limited resources, and security concerns brought on by the use of several devices which are discussed in the paper.

Retracted: B-Ultrasound Image Analysis of Intrauterine Pregnancy Residues after Mid-Term Pregnancy Based on Smart Medical Big Data.

[This retracts the article DOI: 10.1155/2022/9937051.].

Modeling and Automation of Data Collection and Processing in a Smart Medical Ward

The study considers modeling and automating the processes of data collection and processing in a smart medical ward. We examined the existing solutions in the field of smart wards. Such solutions allow to increase patient safety, improve the quality of their treatment, optimize workflows in inpatient facilities, reduce costs and increase comfort of the patients. At the same time, these solutions are focused on particular tasks, use varied technologies and protocols, and implement single scenarios for the functioning of the ward. This is not enough to create an integrated approach to automating patient treatment in smart wards, as there are problems of compatibility and integration of heterogeneous modules, systems and protocols, which leads to growing costs and reduced profitability. To avoid these problems, the complex must be implemented within a single framework with typical components, connections, and operation scenarios. To do this, at the first stage of the work, a conceptual model of a smart room is proposed, a description of its components is given, and scenarios of their functioning are provided. An algorithm for collecting and processing data for diagnosis and stratification of diseases has also been developed, a simulation of the smart ward operation has been carried out, and it showed that the implementation of data collection and processing using smart components can reduce the processing time at least twice.

Retracted: Discuss the Application of Data Services in Data Health Management of High-Risk Pregnant and Lying-In Women in Smart Medical Care.

[This retracts the article DOI: 10.1155/2022/5957697.].

Retracted: Surgical Strategy and Prognosis of Pancreatic Neuroendocrine Tumors Based on Smart Medical Imaging.

[This retracts the article DOI: 10.1155/2022/8752375.].

Retracted: Privacy Protection of Medical Service Data Based on Blockchain and Artificial Intelligence in the Era of Smart Medical Care

Retracted: Privacy Protection of Medical Service Data Based on Blockchain and Artificial Intelligence in the Era of Smart Medical Care