Healthcare Technology Letters最新文献

{"title":"The Role of National Cultural Dimensions in Pandemic Outcomes: A Cross-Sectional Study Across 90 Countries During the COVID-19 Pandemic.","authors":"Han-Hsin Chou, Ru-Shuo Sheu, Chin-I Chiang","doi":"10.1049/htl2.70076","DOIUrl":"https://doi.org/10.1049/htl2.70076","url":null,"abstract":"<p><p>This paper contributes to a relatively simple and efficient referencing method for a decision-maker needs to impose or adjust the policies in fighting against a pandemic crisis. A Bayesian network (BN) model is built via referring to a pre-condition evaluated by canonical correlation analysis to diagnose the likelihood of a severe pandemic by exploring the relationship between Hofstede's national culture dimensions and mortality rate (MR) as well as some other policy-related index. Sample data retrieved from 90 countries and areas up to 13, July 2020, were used for this worldwide cross-sectional study during the COVID-19 pandemic. Another four countries and areas were employed to examine the accuracy of our model. Results also suggest that a strict isolation policy (PI) is possibly not an efficient way to contain the COVID-19 pandemic, especially for those countries or areas with loose ties between individuals. The probability of a high MR, derived from three Hofstede cultural dimensions using the BN model, serves as a reliable indicator of policy implementation effectiveness. Additionally, the individualism versus collectivism (IDV) dimension, which reflects societal group integration (with lower IDV values indicating stronger cohesion), constitutes a key metric for policy assessment. The findings are intended to provide a foundation for developing strategies that strengthen preparedness and resilience in addressing comparable public health crises in the future.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":"e70076"},"PeriodicalIF":3.3,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13054523/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147639809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research and Application of Multi-Link Aggregation Algorithm Based on Link Priority for Telemedicine in Complex Environments.","authors":"Ruiqing Wang, Desen Cao, Jianpeng Ran, Jing Dong, Jun Ma, Xiaowei Yang, Tao Li, Kunlun He","doi":"10.1049/htl2.70061","DOIUrl":"https://doi.org/10.1049/htl2.70061","url":null,"abstract":"<p><strong>Background and objective: </strong>Telemedicine has been introduced as a new and effective method in dealing with public health challenges, improving access to health care, and reducing healthcare costs in today's world. In order to solve the problems of a single access network and the unknown network status of the telemedicine system in complex environments, a multi-link aggregation algorithm based on link priority (MLA-LP) was proposed.</p><p><strong>Methods: </strong>Firstly, the network parameters, such as packet loss rate (PLR) and round-trip time (RTT), of each link were obtained, and then MLA-LP was realized by using the congestion control algorithm based on sender and the traffic allocation algorithm based on link priority. Finally, the MLA-LP algorithm was tested on the test platform based on HoloWAN 1200 network simulator. The comparison algorithm was the multilink aggregation algorithm based on the weightedround-robin algorithm (MLA-WRR).</p><p><strong>Results: </strong>MLA-LP algorithm has higher uplink throughput than MLA-WRR under the same link PLR and delay. When the link is suddenly abnormal (burst packet loss, delay, etc.), the MLA-LP algorithm could quickly avoid the abnormal link and transfer traffic within 2 s; In the mobile scenario, compared with a single network and MLA-WRR algorithm, MLA-LP algorithm has the best video transmission effect, with an average delay of 136 ms, an average bit rate of 2.31 Mbps, an average PLR of 0.04%, and video jamming times close to 0.</p><p><strong>Conclusions: </strong>The MLA-LP algorithm could effectively aggregate link bandwidth and quickly avoid abnormal links, ensuring the robustness of the access network.In order to solve the problems of a single access network and the unknown network status of telemedicine system in complex environment, a MLA-LP was proposed. MLA-LP algorithm has higher uplink throughput and could quickly avoid the abnormal link and transfer traffic within 2 s, ensuring the robustness of the access network.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":"e70061"},"PeriodicalIF":3.3,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12936703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147327631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Study of MR-Guided Needle Insertion for Surgical Procedures: Insights From HoloLens 2, Magic Leap 2 and Apple Vision Pro","authors":"Amaia Iribar-Zabala,&nbsp;Joseba Ruiz-Olalla-Del-Fresno,&nbsp;Inés Rubio-Pérez,&nbsp;Rafael Moreta-Martínez,&nbsp;Andoni Beristain-Iraola,&nbsp;Javier Pascau,&nbsp;Mónica García-Sevilla","doi":"10.1049/htl2.70037","DOIUrl":"10.1049/htl2.70037","url":null,"abstract":"<p>Numerous minimally invasive procedures, including biopsies, ablations and neurostimulation, rely on the accurate placement of a needle under image guidance. Mixed reality (MR) head-mounted displays (HMDs) offer a promising solution to enhance the guidance of these procedures without radiation. While the performance of the established HoloLens 2, now discontinued, is well-documented, the clinical viability of its potential successors remains unproven. This study provides the first direct comparative benchmark of the HoloLens 2, Magic Leap 2 and Apple Vision Pro for a high-precision needle insertion task, using sacral nerve stimulation (SNS) as a validation scenario. We developed custom applications for each platform and evaluated the performance with 11 users, including nine clinicians without prior HMD experience, through a randomized protocol. Quantitative and qualitative analyses were conducted to assess procedural efficiency and user experience. Results identified the Magic Leap 2 as the most effective platform, demonstrating significantly higher success rates and superior usability scores, driven by its ergonomic design and stable tracking. In contrast, the Apple Vision Pro, despite offering superior visual fidelity, proved unsuitable for this navigation task. Its performance was critically hampered by unstable marker tracking, significant device weight, and a lack of accommodation for prescription glasses, which disrupted the clinical workflow. The HoloLens 2 performed as a reliable, albeit less usable, baseline. We conclude that, for this surgical navigation purpose, the optimal HMD is determined by a balanced combination of tracking reliability, user comfort, and practical workflow integration, over the technical specifications of the device. These findings emphasize the importance of device selection in enhancing procedural outcomes and clinical training.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12934502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Free-Standing to Textile Electrodes: Carbonaceous Biocompatible Material for Wearable Sensing","authors":"Marta Vegas-García,&nbsp;Anandapadmanabhan Ambily Rajendran,&nbsp;Beatriz L. Garrote,&nbsp;Daniel Valero Beltrá,&nbsp;Laura García-Carmona,&nbsp;Alfredo Quijano-López,&nbsp;Marta García-Pellicer","doi":"10.1049/htl2.70071","DOIUrl":"10.1049/htl2.70071","url":null,"abstract":"<p>Wearable electronics have been on the rise for personal monitoring in healthcare and sports, allowing real-time tracking. However, developing flexible, conductive, biocompatible, and suitable for continuous, long-term use (bio)electrodes remains a challenge. In this sense, carbon materials offer a promising solution due to their excellent electrical conductivity, mechanical strength, and natural biocompatibility. Moreover, they are cost-effective, modifiable, and align well with environmentally friendly practices. This work presents a simple and sustainable fabrication method for custom-formulated carbon black-chitosan (CB-CH) ink, enhanced with multi-walled carbon nanotubes (MWCNTs). The formulation avoids toxic chemicals, high energy input, and lengthy processing, supporting a greener approach. The resulting ink enables the fabrication of free-standing and textile-based electrodes with high conductivity, mechanical durability, and application-dependent biocompatibility, supporting extended use for CB-CH and short- to medium-term wearable applications (≤24 h) when MWCNTs are incorporated. Their performance was validated through real-time monitoring of electrophysiological signals such as electrocardiograms and electromyograms, showing signal quality comparable to conventional silver electrodes while overcoming gel dehydration and skin irritation. Overall, this work offers a scalable, cost-effective, and eco-friendly pathway for producing multifunctional electrodes, paving the way for next-generation wearable sensing platforms in clinical diagnostics, rehabilitation therapies, and athletic performance monitoring.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12930293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147291344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OpthaNet: Attention-Integrated Architecture for High-Precision Multi-Class Ophthalmic Image Classification","authors":"Souhardo Rahman,&nbsp;Md. Nasif Safwan,&nbsp;Mahamodul Hasan Mahadi,&nbsp;Md. Iftekharul Mobin,&nbsp;Muhammad Firoz Mridha","doi":"10.1049/htl2.70067","DOIUrl":"10.1049/htl2.70067","url":null,"abstract":"<p>This study investigated the efficacy of pre-trained deep learning models for multi-class classification of eye diseases, namely cataract, diabetic retinopathy, and glaucoma, using fundus images. Although CNN and transformer-based models have been extensively explored separately in ophthalmic diagnostics, a direct comparative analysis remains limited. Moreover, recent high-performing systems frequently rely on heavy backbones, ensembles, or large-scale domain pretraining, which can be impractical for resource-constrained screening pipelines. We evaluated three models, EfficientNetB3, MobileNetV2 and vision Transformer, with tailored modifications. An attention-enhanced feature refinement module and the OpthaHead custom classifier enhanced EfficientNetB3 and MobileNetV2, while META customization optimized vision Transformer. The proposed design explicitly targets two practical bottlenecks observed in ophthalmic transfer learning, insufficient feature selectivity for subtle lesions and structural regions, and overfitting or instability in the final decision layers when training data are limited. The optimized EfficientNetB3 achieved a 10.84% improvement over its baseline with 96.04% accuracy, and MobileNetV2 improved by 11.26%, balancing accuracy and computational efficiency. META customization boosted vision Transformer performance by over 18%, showing that reducing model complexity benefits transformers on limited medical data. This study demonstrates strong performance for AI-driven eye disease classification and highlights the potential of AI tools for early detection, improving clinical decision-making and patient outcomes.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12928125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147285434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Informing the Development of Reminiscence Technology for Older Adults: A Prospective Study of Acceptance Determinants","authors":"Gillian Zitrin,&nbsp;Emmanuel Monfort","doi":"10.1049/htl2.70066","DOIUrl":"10.1049/htl2.70066","url":null,"abstract":"<p>Digital health technologies offer promising avenues for supporting the psychological health of the ageing population. Reminiscence therapy, a non-pharmacological intervention, holds significant potential when delivered via digital platforms. This study investigates the factors influencing the acceptance and intention to use a digital reminiscence platform among older adults. We employed an online questionnaire administered to 56 participants aged 60 to 86 years. The study integrated constructs from the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), alongside an assessment of functional reminiscence types. Our findings indicate that perceived usefulness and hedonic motivation are the primary predictors of older adults' intention to use the digital reminiscence platform. Furthermore, functional reminiscence types, specifically integrative and instrumental reminiscence, showed strong associations with higher platform acceptability. These findings highlight the importance of designing digital reminiscence tools that align with older adults’ psychosocial goals and provide meaningful, enjoyable experiences. In particular, perceived usefulness, hedonic motivation, and the relevance of instrumental and integrative reminiscence functions emerged as key acceptance factors. These insights will inform an ongoing co-design process to develop a user-centred platform that supports memory sharing, personal meaning-making, and intergenerational connection.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12927988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147285486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering People With Haemophilia: A Mobile Solution for Self-Management","authors":"Arezou Azizi Alavijeh,&nbsp;Khadijeh Moulaei,&nbsp;Mohammad Mehdi Ghaemi,&nbsp;Kambiz Bahaadinbeigy","doi":"10.1049/htl2.70070","DOIUrl":"10.1049/htl2.70070","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Aims</h3>\u0000 \u0000 <p>Haemophilia is a congenital bleeding disorder requiring extensive self-management. Mobile applications can support these processes. This study aimed to design and evaluate a mobile application to facilitate self-management in persons with haemophilia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study was conducted in two phases. First, a literature review was performed in PubMed, Web of Science, and Scopus, and searches were made in Google Play, Apple Store, and the websites of the World Federation of Hemophilia and Hemophilia Federation of America to identify information-educational needs and necessary capabilities for app design. A questionnaire based on these needs was then provided to physicians and patients for approval. In the second phase, the application prototype was designed according to the approved information-educational needs and necessary capabilities and evaluated for usability using the standard Questionnaire for User Interface Satisfaction with 17 patients. Data were analysed using SPSS 20.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Sixty-two information-educational needs and capabilities with scores above 50% were included in the design. The designed application can provide the conditions for recording demographic information, medical history, treatment information, bleeding information, and injuries and accidents and provide the education on self-management for patients. Moreover, it has the capabilities to set various reminders (taking medication, rehabilitation-physical activities, and appointments with the therapist), set the treatment plan, send reports to the therapist, communicate with other persons with haemophilia and therapists, and record notes. Patients evaluated the application's usability at a “good” level.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The haemophilia self-management app can enhance patients’ quality of life by addressing their educational needs and supporting self-management.</p>\u0000 </section>\u0000 </div>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12916018/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146228945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E-Variance: An Application to Assure Clinical Data Integrity and Improve Patient Safety and Workflows in Electronic Medical Records","authors":"Shafiq Rahman,&nbsp;Konstantin Milman,&nbsp;Taek-Soo Lee","doi":"10.1049/htl2.70069","DOIUrl":"https://doi.org/10.1049/htl2.70069","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Ensuring critical data integrity practices are often missing from the confidence of decision-making in the recorded clinical data. Thus, we developed an application to report clinical data errors to provide effective healthcare IT services and maintain clinical data integrity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>The RadOnc E-Variance web-based application was designed and developed to report data inconsistencies and variances noted during clinical operations. The data inconsistency issues can be reported in 3 broad categories: Patient-related, Non-Patient related, and other suggestions/open-ended, allowing uploading of images or document files. The contents presented on the web are dynamically created in the application and are stored in a database. In the back-end, data analytics and detailed assessments are available on the dashboard. Users reporting variances remain anonymous to ensure reporting freely and frequently.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Once implemented clinically, we have found significant improvements with fewer errors, ensured patient treatment safety, and improved workflows in our state-wide clinics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The RadOnc E-Variance application effectively increases patient safety by ensuring data integrity and minimises risks in the EMR applications at multifaceted enterprise levels of hospital environments by reducing the inconsistencies in data recording and errors recorded in electronic health records.</p>\u0000 </section>\u0000 </div>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/htl2.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146217323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hybrid Ensemble Approach for Early-Stage Diabetes Detection","authors":"Rachana Katuwal KC,&nbsp;Su Yang","doi":"10.1049/htl2.70060","DOIUrl":"10.1049/htl2.70060","url":null,"abstract":"<p>Diabetes has become a critical global health concern, particularly in regions where access to diagnostic facilities is limited. In this work, we propose a hybrid framework that combines extreme gradient boosting (XGBoost) and deep neural networks (DNNs) for early-stage diabetes detection, using soft voting to generate the final ensemble predictions. The proposed framework was evaluated on two datasets: the widely used Diabetes UCI dataset and a newly collected dataset from Nepal. The ensemble method achieved 99% accuracy (ACC) with an area under the curve (AUC) of 1.00 on the Diabetes UCI dataset, and 91% ACC with a 0.96 AUC on the Nepal diabetes dataset, demonstrating its strong generalisability across distinct populations. Compared to individual models, the hybrid approach offered increased stability and a lower rate of false negatives, which is particularly important in clinical contexts. These findings highlight the potential of hybrid machine learning–deep learning models as cost-effective, scalable and generalisable decision-support tools for diabetes risk assessment.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12905728/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Efficient Identification of Retinal Diseases: A Lightweight Convolutional Neural Network-Based Approach Using Optical Coherence Tomography","authors":"Utsab Saha,&nbsp;Puja Saha,&nbsp;MD Jahin Alam,&nbsp;Maruf Ahmed","doi":"10.1049/htl2.70059","DOIUrl":"10.1049/htl2.70059","url":null,"abstract":"<p>Retinal diseases are a major cause of both temporary and permanent vision loss, making early detection and treatment essential to prevent irreversible damage, as the retina's ability to transmit light signals to the brain can be compromised. While deep learning has shown strong potential in diagnosing such conditions using optical coherence tomography (OCT) images, many existing models are highly complex and computationally intensive, making them impractical for deployment on edge devices in clinical settings. To address this issue, we propose a diagnostic framework based on a lightweight deep-learning architecture specifically designed for efficient retinal disease detection. Our model integrates two key components: a lite convolution block, utilizing depthwise separable convolutions for computational efficiency, and a global-local fusion block, which captures both fine-grained local and contextual global features. A squeeze-and-excitation mechanism further refines channel-wise feature importance, all while keeping the parameter count to only 0.27 million. We evaluate our model on three benchmark datasets-OCT 2017, OCT C8 and OCTDL- achieving accuracies of 99.70%, 95.00% and 97.26%, respectively. Our approach demonstrates strong and stable performance validated by confusion matrix and ROC analysis, while Grad-CAM visualizations enhance interpretability, collectively aiming to offer a practical and efficient solution for real-time retinal disease diagnosis.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"13 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12896433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}