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.

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.

Preconception Care Health Education for Female Workers of Reproductive Age in Japan Evaluation up to 6 Months after the Program

Objectives: The aim of this study was to implement a health education program for education of preconception care (PCC) for female workers of reproductive age through a seminar and to evaluate the program based on PCC knowledge and awareness and behaviors before the seminar and at 3 and 6 months after the seminar. Methods: A small group health education seminar was implemented using leaflets for 84 female workers of reproductive age, age 20 to 35 years old, and an intervention by group discussion and feedback was provided. Of these participants, 60 (71%) who provided valid survey responses were included in the analysis. The primary outcome indicators were PCC knowledge, PCC awareness and behaviors, and a food frequency questionnaire, and the secondary outcome indicators were self-efficacy and the health awareness and stress management subscales of the Health-Promotion Lifestyle Profile scale. The survey was conducted three times, before the seminar and at 3 and 6 months after the seminar, and the results were compared. Results: The percentage of individuals with PCC knowledge was significantly increased at 3 months after the seminar as compared with before the seminar, and it remained at this level even at 6 months after the seminar. The percentage of individuals with PCC awareness and behaviors was significantly increased for the items actively eat foods containing folic acid, prevent sexually transmitted diseases, and conduct self-examinations for breast cancer at 3 months after the seminar and for the items eat well-balanced meals, make the mind active, prevent sexually transmitted diseases, and conduct self-examinations for breast cancer at 6 months after the seminar. Furthermore, the score for the health awareness subscale of the Health-Promotion Lifestyle Profile scale was significantly increased at 6 months after the seminar. Conclusion: The health education program established PCC knowledge at 6 months after the seminar and improved some PCC awareness and behaviors. Therefore, it was suggested that the program would be effective for education of PCC for female workers of reproductive age.

Health care exploration work for the military empty nest old cadres

In recent years, the retired veteran cadres have grown older and older, and their numbers have also increased year by year. In this case, how to maintain the physical and mental health of empty nest veteran cadre, and further improve the quality of their life has been a realistic problem many primary health care doctors have to face and solve.

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.

Quality indicators for the care of older adults with disabilities in longterm care facilities based on Maslow’s hierarchy of needs

Purpose:This study aimed to develop quality indicators for the care of older adults with disabilities in long-term care facilities(LTCFs)based on Maslow’s hierarchy of needs.Methods:The draft of the quality indicators was drawn up based on a literature review and research group discussion.The quality indicators were finalized by two rounds of expert consultation(involving 15 experts)using the Delphi method.The Analytic Hierarchy Process was applied to calculate the indicators’weight.Results:The response rates of the two rounds of consultation were 100%and 93%,and the expert authority coefficients were 0.86 and 0.87.After two rounds of consultation,the expert opinion coordination coefficients of the first-,second-and third-level indicators were 0.42,0.25,and 0.96,respectively(P<0.05),and the variation coefficient was0.25.The final quality indicators for the care of older adults with disabilities in LTCFs included 7 first-level,19 second-level,and 107 third-level indicators.Conclusion:The quality indicators for the care of older adults with disabilities in LTCFs are reliable,scientific,comprehensive,and practical and specify the content of person-centered care needs.This can provide a reference for evaluating and improving care quality in LTCFs.

A family nurse-led intervention for reducing health services’utilization in individuals with chronic diseases:The ADVICE pilot study

Objectives:Intensive health services'utilization is common in older individuals affected by chronic diseases.This study assessed whether a structured family nurse-led educational intervention would be effective in reducing health services'use(readmissions and/or emergency service access)among older people affected by chronic conditions.Methods:This is a non-randomized before-after pilot study.A sample of 78 patients was recruited from two general practices in Italy and 70 among them were followed for 8 months.Standard home care was provided during the first four months'period(months 1-4),followed by the educational intervention until the end of the study(months 5-8).The intervention,based on the teach-back method,consisted of by-weekly 60-min home sessions targeting aspects of the disease and its treatment,potential complications,medication adherence,and health behaviours.Rates of health services'use were collected immediately before(T0),and after the interventions(T1).Differences in utilization rates were examined by the McNemar's test.Potential factors associated with the risk of health services'use were explored with a Cox proportional hazard regression model.Results:The sample(n=78)was predominantly female(n=50,64.1%),and had a mean age of 76.2(SD=4.8)years.Diabetes mellitus was the most frequent disease(n=27,34.6%).McNemar's test indicated a significant reduction in health services'use at T1(McNemar χ^(2)==28.03,P<0.001).Cox regressions indicated that time and patient education,as well as their interaction,were the only variables positively associated with the probability of health services'use.Conclusion:A teach-back intervention led by a family nurse practitioner has the potential to reduce health services'use in older patients with chronic diseases.

Art making and expressive art therapy in adult health and nursing care:A scoping review

Objectives:While receptive art engagement is known to promote health and wellbeing,active art engagement has not been fully explored in health and nursing care.This review is to describe the existing knowledge on art making and expressive art therapy in adult health and nursing care between 2010 and 2020.Methods:Relevant studies and grey literature were searched and identified between March 17 and April 10,2020 from EBSCO,CINAHL,Medline and ERIC databases and a general Internet search.Following data charting and extraction,the data(n=42 papers)were summarized and reported in accordance with PRISMA-ScR guidelines.Results:In the included papers,both art making and expressive art therapy were seen in different health care and nursing contexts:yet not the home care context.The emphasis of art activities were group activities for chronically or terminally ill residents,adults aged 65 years or older.A focus on personal narrative was often seen,which may explain why art activities appear to be linked to acknowledging and building new strengths and skills,making meaning of experiences,personal growth,symptom alleviation,and communication;all used to foster collaboration between patients,patients’near-ones and health care professionals.Conclusions:Art activities appear to be suitable for every context and can promote personcenteredness and the measurement of nursing outcomes,and they should be considered an essential part of health and nursing care,nursing education and care for health care personnel.

Health Care Policy and Reform—Case Study on Liberia Tuberculosis among Childbearing Age Women

Objective: Liberia health care needs to focus on addressing this disease called Tuberculosis among childbearing age women in Liberia and the world;focusing on women’s health governance of Liberia should involve these three sets of actors to control a disease outbreak. The first set of state actors, including politicians, policymakers, and other government officials, need to provide health care education in every part. The public sector health bureaucracy comprising the health ministry, health, social insurance agencies, public pharmaceutical procurement and distribution entities, etc., is central. Still, non-health public sector actors also play a role. Methods: The researcher used the questionnaire method as the main instrument for the study. Results: This survey indicates that 48% of those responding to health education can reduce TB among childbearing age women showed that education could minimize the spread of TB. 25% can improve economic status. 27% said it could reduce the illiteracy rate. The instruments used were positively related to the topic to obtain the needed findings. This set comprises public, private, should not be-for-profit individuals and groups that deliver health services and organizations that support service provision: medical training institutions, health insurance agencies, the pharmaceutical industry. Health service delivery can be presenting from the health system perspective, with inputs, processes, outputs, and outcomes. WHO’re Systems Thinking for Health Systems Strengthening explaining that service delivery includes “effective, safe and quality personal and non-personal health interventions that are providing to those in need, when and where needed (including infrastructure), with minimal waste of resources”. Conclusion: Inputs for a sound health system, the need for health care delivery include financial resources, competent health care staff, adequate physical facilities and equipment, essential medicines and supplies, current clinical guidelines, and operational policies.

Identifying Where the Values Come from IT-Innovations in Health and Social Care

Studies aimed to capture the effects of IT-innovations in health and social care have shown that there is a gap between expected and factual outcomes. Many decision makers feel the need to articulate an ideal end-state for their organiza-tions. Striking the balance between novelty and believability of such an ideal end-state is often tricky and they become neither satisfied with the ideal not the visioning. In this study, we explore the contribution of IT-innovations to health and social care. The results showed that coherence between context and IT-innovation is important to capture effects and outcomes. Being coherent rather than visionary contributes to identify where you are, as an organization, and to capture effects and outcomes that “make sense” in the context in question. The paper makes an exposition from the model building, algorithm design to performance analysis and contributes to the academic prosperity in Intelligent In-formation Management The knowledge generated is expected to provide input when identifying goals that IT-investments are supposed to achieve.

On Computing the Suitability of Non-Human Resources for Business Process Analysis

Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service.Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task.In continuation of our previous work,we categorize resources into human and non-human resources.For instance,in the healthcare domain,human resources include doctors,nurses,and other associated staff responsible for the execution of healthcare activities;whereas the non-human resources include surgical and other equipment needed for execution.In this study,we contend that the two types of resources(human and non-human)have a different impact on the process performance,so their suitability should be measured differently.However,no work has been done to evaluate the suitability of non-human resources for the tasks of a process.Consequently,it becomes difficult to identify and subsequently overcome the inefficiencies caused by the non-human resources to the task.To address this problem,we present a three-step method to compute a suitability score of non-human resources for the task.As an evaluation of the proposed method,a healthcare case study is used to illustrate the applicability of the proposed method.Furthermore,we performed a controlled experiment to evaluate the usability of the proposed method.The encouraging response shows the usefulness of the proposed method.

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.

Professional Domiciliary Oral Care for Elderly in Nursing Homes—A Randomized Controlled Pilot Trial

Domiciliary dental care (DDC) makes regular dental visits possible for people with different functional limitations who otherwise would not be able to access a dental clinic. DDC also facilitates cooperation with nursing staff. To our knowledge, the effect of DDC on oral health among elderly people in nursing homes has not been studied. As part of a project to establish recommendations for DDC, the aim of this randomized, controlled, single-blind, pilot trial with three parallel arms was to study the effect of professionally conducted oral care intervention, in domiciliary setting, on gingival bleeding on probing, dental plaque and oral mucosa. For three months, the participants were given either A) monthly professional DDC with oral care intervention, B) monthly individual oral care instructions, or C) oral care as usual. A total of 102 (n = 107) individuals completed the study. After three months, gingival bleeding on probing was significantly reduced among more participants in groups A and B compared with group C (p < 0.0004). Dental plaque scores changed significantly over three months for group B compared with group C (p < 0.04). Mucosal-plaque scores were significantly reduced in group A compared with both group B and C (p < 0.0001). All other intergroup differences were statistically non-significant. Compared with care as usual, professional DDC has the most favourable effect on gingival bleeding, whereas individual oral care instructions result in the highest reduction of dental plaque. Both professional oral care interventions and individual oral-hygiene instructions should be included in a domiciliary oralcare programme.

Exploring the Implementation of Individual Care Plans in Relation to Characteristics of Staff

The aim was to explore the implementation of individual care plans in municipal elderly care in relation to characteristics of staff. Data regarding characteristics of staff were derived through a questionnaire distributed to all staff working in the care for older people, (N = 908, n = 245) in four municipalities in Sweden. The number of care plans established during a one-year period was collected through a contact person in each municipality. In total 47 individual care plans were established during the study year. Significantly more staff in the municipality that had the most number of established individual care plans agreed that there had been sufficient education (p = 0.017), sufficient time (p = 0.002) and routines established regarding individual care plans (p = 0.014) and had a significantly better job satisfaction (p = 0.001), compared to staff in the other municipalities. Implementation leaders may need to take the working conditions and the perception of available resources among staff into consideration in the on-going process of implementing individual care plans.

The patients’ opinion on the use of information technologies at the Seskine Outpatient Clinic and “Centro poliklinika” Outpatient Clinic of the city of Vilnius according to the age of patients

Objectives: The objective of this study is to assess patients’ opinion of the information technologies (IT) electronic registration systems at the “Centro poliklinika” and Seskine outpatient clinics in Vilnius City. Material and Methods: The survey was conducted in May-June, 2012. In the course of the primary survey, one questionnaire was handed out to one in tenth of the newly arrived patients. Total number of 650 questionnaires was distributed. 563 respondents participated in the survey (feedback rate—86.6%). Statistical analysis of data was performed by means of personal computer using SPSS software package. Results: 54.7% of respondents state that they make use of the possibility of online registration with the family doctor. 85.05% of respondents indicate that a doctor, when making the next appointment or referring to the medical specialist, registers a patient on site by means of computer. Upon arrival of a respondent to the reception desk of the medical establishment, 90.3% of respondents are registered by means of computer. 72.4% of respondents say that they have a choice to telephone and inquire about the time of visit if they have forgotten the visit time or lost the appointment sheet. Majority of respondents using the online registration option belong to the age group between 21 and 40 years—35.3%. Conclusions: Answers by the respondents and the breakdown between “Centro poliklinika” and Seskine outpatient clinics are very similar and no essential differences have been determined.

Revolutionizing Treatment:AI-Driven Noninvasive Approaches for ODD and ADHD

Oppositional Defiant Disorder(ODD)and Attention Deficit/Hyperactivity Disorder(ADHD)are mental health conditions that have traditionally been managed through behavioral therapies and medication.However,the integration of Artificial Intelligence(AI)has brought about a revolutionary shift in treatment approaches.This article explores the role of AI-driven noninvasive treatments for ODD and ADHD.AI offers personalized treatment plans,predictive analytics,virtual therapeutic platforms,and continuous monitoring,enhancing the effectiveness and accessibility of interventions.Ethical considerations and the need for a balanced approach are discussed.As technology evolves,collaborative efforts between mental health professionals and technologists will shape the future of mental health care for individuals with ODD and ADHD.

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。

人工智能应用于中医药临床研究的现状

目的梳理人工智能在中医药临床研究中的应用现状,为充分发挥人工智能在中医药研究领域的作用提供参考依据。方法检索中国知网、万方、中国科技期刊数据库、PubMed和Web of Science核心数据库,收集公开发表的针对人工智能在中医药临床研究中应用的文献,进行分析。结果最终纳入32篇文献,均来自中国,发文年限在2014—2023年。研究主要来自高校和医疗机构。纳入的文献均为观察性研究,共包含病例47564例。人工智能在中医药临床研究中的应用包含10个方面,排名前三的分别为:(1)根据中医证型预测疾病发生风险,预测准确率均在80%以上;(2)预测疾病的中医证型,预测准确率高达99.16%;(3)利用人工智能探索疾病的中医证型与理化指标的关联,准确率最高达96.4%。其余7个分别为利用人工智能挖掘并构建了舌图像与疾病的关联模型、辅助诊断、根据中医人格及体质预测疾病发生风险、预测疾病预后、根据中医脉象信号预测疾病发生风险、预测中成药不良反应发生率。结论人工智能在中医药临床研究中赋能效果明显,可有效提高患者的诊疗质量,避免医疗资源的浪费。

“岗课赛证”融通下的高职智慧健康养老服务与管理专业人才培养模式研究与实践

当前,我国养老服务产业进入新蓝海,为高职养老服务类专业提供了广阔的发展空间,但与用人需求相对应的是,高职智慧健康养老服务与管理专业发展还存在供需不匹配、岗课不对接、留存不理想、认同不到位等问题,通过推进“岗课赛证”综合育人改革,进一步优化顶层设计、深化产教融合、强化以赛促学、推行以证代评、健全体制机制,可为养老服务产业培养和输送大批高素质复合型技术技能人才。

智慧康养服务模式下认知症老人服务质量提升的路径探析

在不断加快的老龄化进程中,认知症老年人数量与日俱增,如何为他们提供高质量、专业化的照护服务成为一项重要的社会议题。智慧康养服务模式作为一种革新的养老服务模式,在改善老年人的照护效果和生活质量方面展现出巨大的潜力,在认知症的预防和早期筛查、认知症的临床诊疗与康复、认知症老年人的居家照护等方面,也提供了新的发展方向。然而,从智慧康养服务供应端看,目前仍存在智慧化程度不突出、服务效益滞后及消费市场活力不够、深层次需求挖掘不足及人文关怀特征欠缺、隐私权可能受损及数据安全性难以保障等发展瓶颈;从需求端看,则存在疾病特征阻碍服务接受度、经济负担限制服务消费积极性、技术焦虑制约服务普及等问题的困扰。有鉴于此,在加强科技与企业创新的广度和深度、深化多方主体间的共享与合作、建立产业标准与服务规范、健全监管与反馈机制的同时,有关各方应增加技术的安全性以保障认知症老年人的权益和安全,增加智慧照护产品的友好性和亲和性,培养认知症老年人及家属的数字素养,发挥医疗和护理人员的专业作用,释放认知症群体消费潜力并激发智慧康养市场活力,从而加快我国认知症老年人照护的智慧化进程。