{"title":"Web Application Security in Digital Health: A Dual Analysis and a Context-Aware OWASP-Based Tool Proposal.","authors":"Ylenia Murgia, Jaime Delgado, Mauro Giacomini","doi":"10.3233/SHTI251554","DOIUrl":"https://doi.org/10.3233/SHTI251554","url":null,"abstract":"<p><p>The adoption of digital technologies in healthcare is growing rapidly, and with it, the associated cybersecurity risks are also increasing. In particular, web applications, which can be used to manage and share sensitive health and personal information, require strong security measures to prevent data breaches and ensure compliance with regulatory standards. This paper investigates the applicability of the Open Web Application Security Project (OWASP) guidelines in the healthcare domain. Through a literature review, we identified the most common security requirements considered and used in Digital Health (DH) technologies and assessed their alignment with OWASP Application Security Verification Standard (ASVS). Furthermore, a questionnaire, involving Italian healthcare facilities and Information Technology (IT) companies operating in the healthcare sector, highlighted a significant gap between the availability of security standards and guidelines, and their actual knowledge and use in practice. Based on these findings, we propose a context-aware tool that guides developers and testers in applying OWASP standards throughout the software development lifecycle. The proposed tool aims to provide tailored security recommendations, structured checklists, and test planning based on application context, offering a practical bridge between frameworks and real-world adoption in clinical environments.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"320-324"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215111","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":"Efficacy of a Self-Monitoring Traffic Light for Weight Control in Patients with Heart Failure in a Telerehabilitation Program.","authors":"Katja Møller Jensen, Mathushan Gunasegarama, Malene Hollingdal, Jens Refsgaard, Birthe Dinesen","doi":"10.3233/SHTI251561","DOIUrl":"https://doi.org/10.3233/SHTI251561","url":null,"abstract":"<p><p>Heart Failure (HF), a life-threatening condition, poses a significant global health challenge. Monitoring patients' symptoms and weight is essential, as key HF symptoms tend to cause weight gain and indicate decompensation. The aim of this study is to evaluate the effect of a traffic light algorithm on home monitoring of weight in HF patients. In the project 'Future Patient - Telerehabilitation of Patients with HF II', HF patients monitored their weight, blood pressure, pulse, steps, and sleep at home. Data has been transmitted to the web portal HeartPortal. Each measurement in the weight overview was color-coded using a traffic light algorithm that would indicate whether the patient's weight changes were within the acceptable range. The patients' monitoring data, along with their questionnaire responses, were then analyzed and interpreted. The analysis of the data suggests that the traffic light was effective in alerting patients to weight changes according to clinical guidelines. Most of the patients noticed the traffic light and understood the significance of the colors. The study demonstrates that the traffic light is an effective tool for alerting HF patients to weight fluctuations. The traffic light provides early warnings, enabling timely interventions, and encouraging patient engagement in understanding the causes behind weight changes.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"355-359"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215115","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":"Towards Community-Based Evaluation of AI in Neurology: Development of a Headache Diagnosis Dataset for Large Language Models.","authors":"Anika Zahn, Sebastian Strauss, Dorian Zwanzig","doi":"10.3233/SHTI251535","DOIUrl":"https://doi.org/10.3233/SHTI251535","url":null,"abstract":"<p><p>Diagnosing headache disorders remains a clinical challenge due to the heterogeneity of headache phenotypes and the absence of objective biomarkers. This study presents a curated dataset of 50 clinical headache case examples, comprising both real (n = 34) and synthetic (n = 16) cases, categorized across 20 diagnoses according to ICHD-3 criteria. The dataset enables the evaluation of large language models (LLMs) for diagnostic accuracy in headache medicine. Three GPT-based models were tested using different prompting strategies, with diagnostic performance assessed at both diagnosis and group levels. Top-1 accuracy ranged from 24% to 63% at the diagnosis level and up to 92% at the group level. The results highlight the potential of LLMs in supporting differential diagnosis of headache disorders, while also emphasizing the need for further validation with larger, diverse datasets. Future efforts will focus on expanding real-world data through clinical collaborations and benchmarking LLMs against medical professionals to assess their utility in clinical decision-making.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"237-241"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215131","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 Care and Human Death: Ethical Tensions at the End of Life.","authors":"Murat Sariyar","doi":"10.3233/SHTI251528","DOIUrl":"https://doi.org/10.3233/SHTI251528","url":null,"abstract":"<p><p>The digitization of healthcare - through electronic health records, predictive algorithms, remote monitoring, and automated decision-making tools - has revolutionized clinical workflows and optimized patient management. However, these developments often carry unintended consequences when applied to the end-of-life context, where the subjective, relational, and existential dimensions of dying resist abstraction and quantification. This paper explores the tensions between digital efficiency and the human realities of death, arguing that the virtuality of digital health systems risks alienating patients, families, and clinicians at precisely the moments where care must be most embodied and relational. Drawing from a conceptual analysis informed by medical ethics and palliative care literature, we examine how virtual representations (data, dashboards, protocols) interact with real dying bodies and social relationships. Through case illustrations, we highlight how systems designed for efficiency can unintentionally marginalize suffering, flatten complex narratives, and displace the rituals and presence that define authentic death. Our findings suggest a pressing need to reorient digital health design to account for the limits of representation and the irreplaceability of human connection at the end of life. We argue that any future model of digital care must not only prioritize outcomes but also preserve dignity, ambiguity, and relational integrity in death.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"206-210"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215141","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}
Shivam Upadhyay, Paulo Haas, Julian Bollmann, Nagarajan Ganapathy, Thomas M Deserno
{"title":"Transmission of Vital Data in Emergencies Using the International Standard Accident Number.","authors":"Shivam Upadhyay, Paulo Haas, Julian Bollmann, Nagarajan Ganapathy, Thomas M Deserno","doi":"10.3233/SHTI251518","DOIUrl":"https://doi.org/10.3233/SHTI251518","url":null,"abstract":"<p><p>During an emergency, fast and reliable transmission of patient vitals improves hospital preparedness and medical responsiveness. The International Standard Accident Number (ISAN) links data from different stages of the rescue chain. We apply the ISAN system for direct communication between the responding system and the curing system. A framework for smart bands - cheap, flexible, and sanitary devices for measuring vital signs - prepares the integration of medical devices in emergency vehicles. We simulate the transmission of a patient's electrocardiogram from the driving rescue vehicle to the hospital's emergency unit, demonstrating reliability and feasibility.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"160-164"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215142","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":"The Use of the Social Robot LOVOT for Children with Autism Spectrum Disorder: A Feasibility Study.","authors":"Anders Bobo Larsen, Rasmus Birk Buhl, Kristina Ørtoft Müller, Birthe Dinesen","doi":"10.3233/SHTI251499","DOIUrl":"https://doi.org/10.3233/SHTI251499","url":null,"abstract":"<p><strong>Background: </strong>One in 100 children is diagnosed with autism spectrum disorder (ASD). Social robots have proven to be a promising technology for children with ASD. The emergence of the social robot LOVOT adds new dimensions to the interaction between robots and children with ASD.</p><p><strong>Aim: </strong>To explore how staff experience using the social robot as a pedagogical tool for children with ASD.</p><p><strong>Method: </strong>This study was conducted at an institution in Denmark that specializes in special education programs for children with ASD. The interactions between children with ASD and the social robot were tested in individual sessions twice per week for a total of four weeks. Four children with ASD between 9-14 years were included (n=4). A triangulation of data collection techniques was used: Participant observation (n = 15 hours), children's questionnaire (n = 4), and semi-structured interviews with staff (n = 3).</p><p><strong>Findings: </strong>Findings can be summarized as follows: Acceptance of the social robot, positive changes in mood and behavior of children with ASD, a secure relationship, technical and practical issues to overcome, and ethical considerations.</p><p><strong>Conclusion: </strong>The professional staff saw a potential for using the robot with AI functionalities as a pedagogical tool for children with ASD.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"77-81"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215160","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":"WearPGHDProvO: An Extension of PGHDProvO for Wearables.","authors":"Abdullahi Abubakar Kawu, Dympna O'Sullivan, Lucy Hederman","doi":"10.3233/SHTI251545","DOIUrl":"https://doi.org/10.3233/SHTI251545","url":null,"abstract":"<p><p>Wearable devices are increasingly used to create patient generated health data (PGHD), yet existing models lack the specificity to fully capture the nuances of this data. This paper presents an initial work on WearPGHDProv, an extension of the PGHDProvO ontology, designed to address this gap. We extended the PGHDProvO ontology using a top-down approach, incorporating concepts from the W3C Provenance Ontology (PROV-O) and domain-specific terms related to wearable devices and data generation. WearPGHDProv introduces new classes and properties to model device-specific information, additional related information unique to wearable data, and the context of data collection. This extension enhances the ability to track the source, pertinent information, and quality of wearable-generated PGHD, facilitating its reliable use in electronic health records (EHRs) and research.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"283-287"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215082","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}
Laura Haase, Ada Rehfeld, Sharleen Schnelle, Sofia Rodriguez
{"title":"Designing mHealth Applications for Anamnesis by Proxy: A Systematic Literature Review of Recommendations.","authors":"Laura Haase, Ada Rehfeld, Sharleen Schnelle, Sofia Rodriguez","doi":"10.3233/SHTI251500","DOIUrl":"https://doi.org/10.3233/SHTI251500","url":null,"abstract":"<p><p>Mobile health (mHealth) applications have become important in modern healthcare, yet tailored design recommendations for third-party anamnesis (anamnesis by proxy) - particularly for lay caregivers of infants and other care-needing individuals - remain limited. This systematic literature review addresses this gap by investigating existing design recommendations for mHealth apps in this context. A comprehensive search was conducted across several databases. The extracted recommendations include e.g. remote support by medical professionals, real-time notifications, information on self-management and conditions, peer support, and non-functional aspects, including ease of use and offline accessibility. The consolidated recommendations aim to assist developers and researchers in creating mHealth applications for third-party anamnesis by lay caregivers.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"83-87"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215098","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":"Validating the HOPT-Fit Evaluation Framework for Health Information Systems via Case Studies.","authors":"Maryati Mohd Yusof","doi":"10.3233/SHTI251504","DOIUrl":"https://doi.org/10.3233/SHTI251504","url":null,"abstract":"<p><p>Health information systems (HIS) have been extensively adopted to reduce medication errors. Unfortunately, complex socio-technical issues in HIS can create new error risks, resulting in unintended patient harm. Rigorous evaluation can therefore provide insights to inform risk factors and mitigation measures. This paper presents the validation methods of a proposed human, organisation, process, and technology-fit (HOPT-fit) framework in multiple qualitative case study evaluations using observation, interview, and document analysis in Japanese and Malaysian clinical settings. Findings validated the HOPT-fit applicability in evaluating HIS effectiveness and safety's complex and dynamic nature.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"98-102"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215135","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}
Johanna Schwinn, Seyedmostafa Sheikhalishahi, Matthaeus Morhart, Iñaki Soto-Rey, Mathias Kaspar, Ludwig Christian Hinske
{"title":"Comparative Federated Analytics of Blood Transfused Patients in Five ICU Databases: Using Kullback-Leibler Divergence.","authors":"Johanna Schwinn, Seyedmostafa Sheikhalishahi, Matthaeus Morhart, Iñaki Soto-Rey, Mathias Kaspar, Ludwig Christian Hinske","doi":"10.3233/SHTI251495","DOIUrl":"https://doi.org/10.3233/SHTI251495","url":null,"abstract":"<p><p>This study assesses feature distribution differences across five intensive care databases using Kullback-Leibler Divergence (KLD). Analyzing bidirectional KLD patterns between individual databases and the composite of others, stratifying by transfusion status. Results reveal heterogeneity: HiRID shows highest divergence in both directions, particularly among transfusion cases; UKA exhibits moderate overall divergence but pronounced differences in transfusion scenarios; MIMIC-IV shows minimal divergence, indicating closest alignment with group distributions. Notably, transfusion cases consistently display higher divergence than non-transfusion cases across all databases, highlighting institution-specific practices. These findings stress the importance of assessing data heterogeneity before implementing federated learning models to understand generalization capabilities.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"332 ","pages":"57-61"},"PeriodicalIF":0.0,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215139","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}