Health and Technology最新文献

{"title":"Developing policy-ready digital dashboards of geospatial access to emergency obstetric care: a survey of policymakers and researchers in sub-Saharan Africa","authors":"Jia Wang, Kerry L. M. Wong, T. Olubodun, Uchenna Gwacham-Anisiobi, Olakunmi Ogunyemi, B. Afolabi, Peter M. Macharia, P. Makanga, I. Abejirinde, Lenka Beňová, A. Banke-Thomas","doi":"10.1007/s12553-023-00793-9","DOIUrl":"https://doi.org/10.1007/s12553-023-00793-9","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"53 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138591134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An artificial intelligent network model to monitor the condition of a patient with a breast tumor based on fuzzy logic","authors":"Javad Nouri pour, M. Pourmina, Mohammad Naser Moghaddasi, B. Ghalamkari","doi":"10.1007/s12553-023-00800-z","DOIUrl":"https://doi.org/10.1007/s12553-023-00800-z","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"5 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138594733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensing health: a bibliometric analysis of wearable sensors in healthcare","authors":"Azliyana Azi̇zan, Waqas Ahmed, Abdul Hadi Abdul Razak","doi":"10.1007/s12553-023-00801-y","DOIUrl":"https://doi.org/10.1007/s12553-023-00801-y","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"57 15","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138597232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Of digital transformation in the healthcare (systematic review of the current state of the literature)","authors":"Mus’ab Muhammad Kakale","doi":"10.1007/s12553-023-00803-w","DOIUrl":"https://doi.org/10.1007/s12553-023-00803-w","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"62 9","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138598432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of machine learning and ensemble approaches for hepatitis B prediction using data mining with synthetic minority oversampling technique","authors":"Azadeh Alizargar, Yang-Lang Chang, Tan-Hsu Tan, Tsung-Yu Liu","doi":"10.1007/s12553-023-00802-x","DOIUrl":"https://doi.org/10.1007/s12553-023-00802-x","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"69 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139214973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data management for resource optimization in medical IoT","authors":"Iqra Jan, Shabir Sofi","doi":"10.1007/s12553-023-00796-6","DOIUrl":"https://doi.org/10.1007/s12553-023-00796-6","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"2 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139217869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainability analysis in predictive models based on machine learning techniques on the risk of hospital readmissions","authors":"Juan Camilo Lopera Bedoya, Jose Lisandro Aguilar Castro","doi":"10.1007/s12553-023-00794-8","DOIUrl":"https://doi.org/10.1007/s12553-023-00794-8","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"14 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139225333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital twins for breast cancer treatment – an empirical study on stakeholders’ perspectives on potentials and challenges","authors":"Jens Konopik, Larissa Wolf, Oliver Schöffski","doi":"10.1007/s12553-023-00798-4","DOIUrl":"https://doi.org/10.1007/s12553-023-00798-4","url":null,"abstract":"Abstract Purpose With 2.3 million diagnoses and 685,000 deaths annually, breast cancer is the most common cancer in women. The provision of necessary information throughout the whole patient journey is key to minimize the risk of breast cancer, to detect breast cancer as early as possible, and to aid the treatment process. Digital solutions provide abilities to holistically collect, transfer, and sophisticatedly analyze information. Specifically, digital twins in healthcare, as dynamic replicas of human bodies, are promising approaches for monitoring the condition of their patients and predicting tumor developments based on biometric data. However, the acceptance and adoption of such digital twin solutions in healthcare heavily depend on the individual stakeholders of the treatment process. This study aims to identify potentials and challenges of the introduction of digital twins in breast cancer applications from the involved stakeholders’ perspectives. Methods We conducted semi-structured interviews with 14 relevant stakeholders from the breast cancer treatment process. The interviews were then analyzed, based on the qualitative content analysis according to Mayring. Results The results show that stakeholders see great potential in digital twin solutions to further facilitate personalized medicine, efficiency increases, and scientific benefits. However, the sensitive nature of healthcare causes numerous potential challenges in the technical, regulatory, user interface, and the strategic domain. Conclusions The stakeholders unanimously agreed on the potential benefits of digital twins. However, existing systemic and individual stakeholder-level barriers hamper their introduction in breast cancer settings.","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"35 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134992662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical relief potential through robot-assisted mobilization in nursing care: an exploratory study","authors":"Jonathan Levin Behrens, Christian Kowalski, Anna Brinkmann, Sara Marquard, Sandra Hellmers, Maren Asmussen-Clausen, Karina Jürgensen, Stephanie Raudies, Manfred Hülsken-Giesler, Andreas Hein","doi":"10.1007/s12553-023-00795-7","DOIUrl":"https://doi.org/10.1007/s12553-023-00795-7","url":null,"abstract":"Abstract Purpose Physically demanding activities at the nursing bed are a key factor in the overwork of nursing staff and play a major role in the development of musculoskeletal disorders. The heavy back strain plays a significant part in this. Technical aids such as robotic assistance systems have the potential to minimize this overload during nursing activities. In the present work, we have investigated the relief potential of a supporting robotic assistance system developed in the AdaMeKoR project. An exploratory study design was developed to assess the relief potential of the robotic system for nurses during the care action of repositioning from the supine position to the sitting position at the edge of a nursing bed under kinaesthetic principles. Methods The study was conducted in March 2022 with a total of 21 nursing professionals participating. Safety precautions at this stage of the robot’s development made it necessary to use a 40 kg patient simulator instead of having a human act as the patient. Each participant performed the repositioning three times in the conventional manner and three times with the robotic-assistance. The conventional and the robotic-assisted task execution was compared using different perspectives of analysis. From a sensory perspective, ground reaction forces and electromyography data were collected and analyzed. A kinaesthetic perspective was added using 3D-video data which was analyzed by professional kinaesthetics trainers. A third perspective was added by collecting the subjective workload experiences of the participants. Results While participants’ self-assessment based on a NASA-TLX questionnaire suggests more of a physical and psychological strain from using the robot, electromyography shows a 24.41% reduction in muscle activity for left back extensors and 7.99% for right back extensors. The kinaesthetic visual inspection of the study participants also allows conclusions to be made that the robot assistance system has a relieving effect when performing the nursing task. Conclusions The conducted study suggests that overall the robotic-assistance has the potential of relieving nurses of partial physical exertion during mobilization. However, the different focuses of analysis show varying results in regard to external, i.e. sensor data and expert analysis, compared to internal, i.e. the nurses, perspectives. Going forward, these results have to be further expanded to get more robust analyses and insights on the interdependencies of subjective factors contributing to the experience of workload. In view of the fact that robotics for nursing is still a relatively new field and there are various lessons to be learned regarding the conceptualization of studies and corresponding evaluations, our approach of combining perspectives of analysis allows for a more differentiated view of the subject at hand.","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"35 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134992834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internet-of-things based machine learning enabled medical decision support system for prediction of health issues","authors":"Manju Lata Sahu, Mithilesh Atulkar, Mitul Kumar Ahirwal, Afsar Ahamad","doi":"10.1007/s12553-023-00790-y","DOIUrl":"https://doi.org/10.1007/s12553-023-00790-y","url":null,"abstract":"","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"75 23","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135037525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}