Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and recovery.The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance.Although many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during analysis.Therefore,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare Monitoring.At first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction process.Here,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable devices.To attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced features.After that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and overhead.Experimental evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several instances.The quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

Aging Characteristics and Layout Planning of Old-age Care Facilities in the Downtown Area of Nanchang City

Compared to the situation of population aging and the elderly aging, the development of oldage undertaking in Nanchang is still undeveloped in that the old-age care industry lags behind the urban renewal speed and the objective needs of aging. Apart from discussions on the composition of elderly population and the status quo of aging, this paper took the institutional old-age care in the downtown area of Nanchang for example, explored problems in the current institutional old-age care facilities through field investigation, and proposed suggestions for the layout planning of old-age care facilities in the study area.

Artificial intelligence:Applications in critical care gastroenterology

Gastrointestinal(GI)complications frequently necessitate intensive care unit(ICU)admission.Additionally,critically ill patients also develop GI complications requiring further diagnostic and therapeutic interventions.However,these patients form a vulnerable group,who are at risk for developing side effects and complications.Every effort must be made to reduce invasiveness and ensure safety of interventions in ICU patients.Artificial intelligence(AI)is a rapidly evolving technology with several potential applications in healthcare settings.ICUs produce a large amount of data,which may be employed for creation of AI algorithms,and provide a lucrative opportunity for application of AI.However,the current role of AI in these patients remains limited due to lack of large-scale trials comparing the efficacy of AI with the accepted standards of care.

Advance IoT Intelligent Healthcare System for Lung Disease Classification Using Ensemble Techniques

In healthcare systems,the Internet of Things(IoT)innovation and development approached new ways to evaluate patient data.A cloud-based platform tends to process data generated by IoT medical devices instead of high storage,and computational hardware.In this paper,an intelligent healthcare system has been proposed for the prediction and severity analysis of lung disease from chest computer tomography(CT)images of patients with pneumonia,Covid-19,tuberculosis(TB),and cancer.Firstly,the CT images are captured and transmitted to the fog node through IoT devices.In the fog node,the image gets modified into a convenient and efficient format for further processing.advanced encryption Standard(AES)algorithm serves a substantial role in IoT and fog nodes for preventing data from being accessed by other operating systems.Finally,the preprocessed image can be classified automatically in the cloud by using various transfer and ensemble learning models.Herein different pre-trained deep learning architectures(Inception-ResNet-v2,VGG-19,ResNet-50)used transfer learning is adopted for feature extraction.The softmax of heterogeneous base classifiers assists to make individual predictions.As a meta-classifier,the ensemble approach is employed to obtain final optimal results.Disease predicted image is consigned to the recurrent neural network with long short-term memory(RNN-LSTM)for severity analysis,and the patient is directed to seek therapy based on the outcome.The proposed method achieved 98.6%accuracy,0.978 precision,0.982 recalls,and 0.974 F1-score on five class classifications.The experimental findings reveal that the proposed framework assists medical experts with lung disease screening and provides a valuable second perspective.

Problems and Countermeasures of Intelligent Elderly Care Service in the Context of Fewer Children in China

With the intensification of population aging and the implementation of the three-child policy,the elderly care pressure of Chinese families continues to rise.Therefore,accelerating the construction of a new intelligent elderly care service model is an important measure to actively respond to population aging,ease the burden of family elderly care and promote high-quality economic development.In view of this,this study analyzed the intelligent elderly care service to explore the relevant countermeasures of the intelligent elderly care service in the context of fewer children.

Analysis of home care-based multi-level old-age service system

With the deepening of China＇s aging, China＇s social pension problem more obvious each day, and gradually become the focus of attention of the whole society. On the one hand, China entered the aging society, old-age needs to grow exponentially. The sixth national census shows that in our country, the population aged 60 and 13.26% of the total population over the total number of 179 million, 65 years and older the proportion of 8.87% of the total population, the absolute number of nearly 120 million. Hundreds of millions of older age groups will produce a growing demand for care services, which is the original old-age service system and the whole economic and social development is a huge pressure. On the other hand, with the economic and social transformation, the traditional model of family pension has been unable to adapt to the profound changes in modem employment, family structure, the concept of retirement, since most parts of China, ＂old before getting ricE＂ the situation, how to solve the elderly the pension problem is related to the overall situation of China＇s economic and social development, related to the overall situation of building a harmonious society in China. Under current national conditions, the emphasis on the development of a single individual body to meet the growing demand for pension service is not realistic, we must mobilize the enthusiasm of all aspects of the element, multi-service integration of resources subject to their commitment to a different responsibilities and tasks provide a full range of care services according to different types, different levels of the actual needs of the older age groups. On the aging problem is that the whole community to face, you need to multi-government body, families, communities, institutions combine effectively starting from the actual needs of the elderly population, according to the financial assistance, life care, spiritual consolation three set the specific needs of services, through a government-led, home-based care services, community care services for the core and supplementary services for institutions focused on pension and other means to provide a full range of pension services.

Construction of Xi'an ecological old-age care community in the new urbanization

The new urbanization is an important carrier of ecological civilization construction, and ecological old-age care is the concrete manifestation of the perfect combination of the two, the proper meaning of the new urbanization connotation and an inevitable trend of its development. Based on the analysis of the connotation and relationship between the new urbanization and ecological old-age care, together with the current situation and existing problems of the current nursing institutions and ecological old-age care in Xi'an area, this paper discusses the major issues that should be noticed when constructing the ecological old-age care community in Xi'an and three main construction modes.

Study on Supply and Demand of Intelligent Home-based Aged Care in Shanghai

The 21st century is an era of aging population. With the accelerated aging of the population in our country, and the grim form of population aging, intelligent home-based care has become a concern for the elderly in the area of ？？care. This paper starts from the new concept of intelligent home-based care services and defines intelligent home care services. It also summarizes the current theoretical researches related to domestic research, which is of great significance for the investigation and research conducted in the later stage of research.

The Experience and Enlightenment of the Development of Old-age Care Services in Russia

Through the analysis of the history and current situation of Russia＇s old-age care services system, this paper analyzes and studies the old-age care services system in Russia. By means of law and social policy, Russia can promote the active participation of the elderly in politics, economy, culture and other activities to promote the positive image of the elderly. The active aging policy in Russia and the development trend of the old-age care service to promote the social adaptation and re-employment of the elderly are of positive significance to the development of our country＇s old-age care service.

The Next Era:Flourish of National Health Care & Medicine with the World Leading Artificial Intelligence

MODERN medical diagnosis and practice heavily rely on biological data and information from patients’ body.The progress of biomedical sensor,material and mathematical technology provided ever-increasing methods to gather data.While providing more choices and more comprehensive picture of patients’ conditions to doctors and practitioners,these progresses also require more labor efforts to read,analyze,and make decisions based on those data.It is very difficult for the medical human resources to grow at a speed that matches such need for diagnosis-related expert knowledge.The shortage of expertise has caused long waiting time for check report and fatal misjudged diagnosis in public health system,and it will compromise our ability to move towards a more precise,more personalized and more efficient future of medicine.

Artificial Intelligence and Autonomous Machines: Influences, Consequences, and Dilemmas in Human Care

In the field of robotics and in the health sciences, transitions have been occurring in the control of robots operating with predetermined logic and rules. Robotics in health care are influencing human caring dynamics in many ways such as enhancing dependency and surrender to machine technologies. Situations such as these are charged with possibilities of legal liabilities triggered by influences and consequences of advancing robotic technology dependency. The purpose of this paper is to identify, describe, and explain legal issues and/or dilemmas centered on robotics in healthcare while providing engaging opportunities to limit consequent legalities thus forming beneficial human health care outcomes. Laying bare these liabilities will provide critically informative data that can foster proactive encounters which can or may deter health care liabilities while ensuring quality healthcare outcomes. An attempt is made to re-conceptualize how to view agency, causality, liability responsibility, culpability, and autonomy for the new age of autonomous robots. While it is still not clear how this would turn out, a clear framing of the problem is the first step in the project.

Predictive modeling in neurocritical care using causal artificial intelligence

Artificial intelligence(AI)and digital twin models of various systems have long been used in industry to test products quickly and efficiently.Use of digital twins in clinical medicine caught attention with the development of Archimedes,an AI model of diabetes,in 2003.More recently,AI models have been applied to the fields of cardiology,endocrinology,and undergraduate medical education.The use of digital twins and AI thus far has focused mainly on chronic disease management,their application in the field of critical care medicine remains much less explored.In neurocritical care,current AI technology focuses on interpreting electroencephalography,monitoring intracranial pressure,and prognosticating outcomes.AI models have been developed to interpret electroencephalograms by helping to annotate the tracings,detecting seizures,and identifying brain activation in unresponsive patients.In this mini-review we describe the challenges and opportunities in building an actionable AI model pertinent to neurocritical care that can be used to educate the newer generation of clinicians and augment clinical decision making.

An Efficient Blockchain-Based Healthcare System Using Artificial Intelligence

Personal health records and electronic health records are considered as the most sensitive information in the healthcare domain.Several solutions have been provided for implementing the digital health system using blockchain,but there are several challenges,such as secure access control and privacy is one of the prominent issues.Hence,we propose a novel framework and implemented an attribute-based access control system using blockchain.Moreover,we have also integrated artificial intelligence(AI)based approach to identify the behavior and activity for security reasons.The current methods only focus on the related clinical records received from a medical diagnosis.Moreover,existing methods are too inflexible to resourcefully sustenance metadata changes.A secure patient data access framework is proposed in this research,integrating blockchain,trust chain,and blockchain methods to overcome these problems in the literature for sharing and accessing digital healthcare data.We have used a neural network and classifier to categorize the user access to our proposed system.Our proposed scheme provides an intelligent and secure blockchain-based access control system in the digital healthcare system.Experimental results surpass the existing solutions by collecting attributes such as the number of transactions,number of nodes,transaction delay,block creation,and signature verification time.

21st century critical care medicine:An overview

Critical care medicine in the 21st century has witnessed remarkable advancements that have significantly improved patient outcomes in intensive care units(ICUs).This abstract provides a concise summary of the latest developments in critical care,highlighting key areas of innovation.Recent advancements in critical care include Precision Medicine:Tailoring treatments based on individual patient characteristics,genomics,and biomarkers to enhance the effectiveness of therapies.The objective is to describe the recent advancements in Critical Care Medicine.Telemedicine:The integration of telehealth technologies for remote patient monitoring and consultation,facilitating timely interventions.Artificial intelligence(AI):AI-driven tools for early disease detection,predictive analytics,and treatment optimization,enhancing clinical decision-making.Organ Support:Advanced life support systems,such as Extracorporeal Membrane Oxygenation and Continuous Renal Replacement Therapy provide better organ support.Infection Control:Innovative infection control measures to combat emerging pathogens and reduce healthcare-associated infections.Ventilation Strategies:Precision ventilation modes and lung-protective strategies to minimize ventilatorinduced lung injury.Sepsis Management:Early recognition and aggressive management of sepsis with tailored interventions.Patient-Centered Care:A shift towards patient-centered care focusing on psychological and emotional wellbeing in addition to medical needs.We conducted a thorough literature search on PubMed,EMBASE,and Scopus using our tailored strategy,incorporating keywords such as critical care,telemedicine,and sepsis management.A total of 125 articles meeting our criteria were included for qualitative synthesis.To ensure reliability,we focused only on articles published in the English language within the last two decades,excluding animal studies,in vitro/molecular studies,and non-original data like editorials,letters,protocols,and conference abstracts.These advancements reflect a dynamic landscape in critical care medicine,where technology,research,and patient-centered approaches converge to improve the quality of care and save lives in ICUs.The future of critical care promises even more innovative solutions to meet the evolving challenges of modern medicine.

On the present and future of medical humanistic care in the era of artificial intelligence

With the arrival of the fourth industrial revolution,the combination of artificial intelligence and medical treatment has become an inevitable trend.As a people-centered discipline,the importance of humanistic care is self-evident.Based on the development status of humanistic care,this paper discusses that when artificial intelligence is applied to medicine,it will help patients improve the treatment process,protect their right to know and expression,help medical personnel deal with repetitive work,improve work efficiency,provide doctors with psychological medical time and enhance doctor-patient trust.At the same time,it will inevitably lead to the lack of emotion in the way of diagnosis and treatment,the threat to the authority of doctors,and the disclosure of patients'personal information.Therefore,in the era of artificial intelligence,doctors should return to the service foundation of humanistic care,"master"the"art of medicine"of artificial intelligence technology,and improve the practical road of laws and regulations.

Unveiling significant risk factors for intensive care unit-acquired weakness:Advancing preventive care

In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World Journal of Clinical Cases.Intensive care unit-acquired weakness(ICU-AW)is a debilitating condition that affects critically ill patients,with significant implications for patient outcomes and their quality of life.This study explored the use of artificial intelligence and machine learning techniques to predict ICU-AW occurrence and identify key risk factors.Data from a cohort of 1063 adult intensive care unit(ICU)patients were analyzed,with a particular emphasis on variables such as duration of ICU stay,duration of mechanical ventilation,doses of sedatives and vasopressors,and underlying comorbidities.A multilayer perceptron neural network model was developed,which exhibited a remarkable impressive prediction accuracy of 86.2%on the training set and 85.5%on the test set.The study highlights the importance of early prediction and intervention in mitigating ICU-AW risk and improving patient outcomes.

Man&Machine:Artificial Intelligence’s Role in Shaping Auditor’s Professional Scepticism

This study aims to investigate how auditors’reliance on artificial intelligence(AI)impacts their professional scepticism in the French auditing profession.While artificial intelligence offers benefits,like improved audit efficiency,concerns arise regarding its potential to reduce scepticism.Using a multiple regression approach with maximum likelihood estimation,we analyzed 107 responses from external auditors.The findings reveal a significant positive association between AI reliance and professional scepticism,moderated by trait scepticism.The study contributes to the existing literature by shedding light on the complex interplay between technological adoption and individual judgment in auditing.It offers insights into the French context and emphasizes the importance of understanding how AI affects professional scepticism among auditors.Additionally,the findings underscore the crucial role of individual auditor traits,such as scepticism levels,in shaping their responses to technological advancements in auditing practices.

智能机器人在基层慢性病管理中的应用与挑战

全球慢性病患病率不断上升,给社会的发展和个人健康带来重大挑战。管理慢性病需要长期治疗和监测,对患者的生活方式提出了一定要求。随着人口老龄化和人们生活方式的改变,慢性病防控正变得越发重要。近年来,随着医疗卫生领域科技创新向纵深发展,借助人工智能的智能机器人在医疗领域的应用也逐渐成为国家重要战略方向之一,传统的慢性病管理方法过于依赖医生和患者之间的线下交流,导致医生无法与患者保持长期且有效的沟通和随访,患者病情出现变化时医生可能无法及时发现和监测。此外,传统的慢性病管理方法通常是一种通用化的方法,无法充分考量到每位患者的个体差异。鉴于传统慢性病管理方法的局限性,本文提倡利用智能机器人提供更便捷高效的基层服务。本文认为,通过个性化健康管理方案、辅助医疗诊断、定时提醒服药等功能,使智能机器人能够致力于改善患者生活质量、减轻医疗资源压力,从而推动全球智能化医疗管理的发展。

糖尿病患者对人工智能电话随访的意愿及需求的质性研究

目的了解糖尿病患者对人工智能电话随访的意愿及需求,为构建更符合实际需求的人工智能电话随访方案提供参考。方法采用描述性质性研究,自拟提纲对2023年12月至2024年5月在广州市某三级甲等医院内分泌科住院治疗的16例2型糖尿病患者进行一对一深入访谈,采用内容分析法分析资料、提炼主题。结果提炼出4个主题:希望接受人工智能电话随访服务;希望人工智能电话随访明确表明医院身份;希望人工智能电话随访提供个性化的随访指导(老年患者个性化随访需求、个性化饮食指导的需求、定制化血糖管理指导、心理支持需求);希望人工智能电话随访和人工随访相结合(融合人工智能与人工随访的需求、对人工随访的期待、多模态信息提供的需求)。结论糖尿病患者希望接受人工智能电话随访。建议医院构建人工智能电话随访系统,为糖尿病患者提供专业和个性化的电话随访服务,并结合人工随访与多模态方法提高随访的可靠性和效果。

数智环境下价值网络对社区养老服务精准化的影响机理研究——基于扎根理论的探索

[目的/意义]精准化是社区养老服务发展的主要目标,是衡量社区养老服务水平的重要标准。当前社区养老服务发展存在供需失衡,服务精准化水平不高。大数据、人工智能等数智环境飞速发展为社区养老服务精准化水平提升带来了历史机遇,而探索社区养老服务精准化水平的影响机理是更加有效提升服务精准化水平的前提。[方法/过程]基于价值网络模型,采用扎根理论研究方法,对社区养老服务相关参与主体代表的半结构化访谈语料进行编码分析,参照“背景-条件-行动-结果”的扎根理论经典范式,分析数智环境下价值网络对社区养老服务精准化的影响机理。[结果/结论]构建影响机理“火箭模型”,从宏观、中观、微观3个层面,分析价值网络对社区养老服务精准化水平的影响因素和作用机理,其中“数智技术赋能”是关键影响因素。研究回答了数智环境下价值网络对社区养老服务精准化的“影响机理是什么”的问题,为后续探索提升服务精准化水平的策略指明方向。