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Information System for Supporting Seafarer's Health Incident Reporting.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250085
Konstantinos Karitis, Emmanouil Zoulias, Joseph Liaskos, John Mantas
{"title":"Information System for Supporting Seafarer's Health Incident Reporting.","authors":"Konstantinos Karitis, Emmanouil Zoulias, Joseph Liaskos, John Mantas","doi":"10.3233/SHTI250085","DOIUrl":"https://doi.org/10.3233/SHTI250085","url":null,"abstract":"<p><p>This research studies and develops an information support system for recording health incidents at sea in T.M.A.S. (Telemedical Maritime Assistance Services) Telemedicine centres. The T.M.A.S. are Telemedical consulting services designed to help and support seafarers and passengers on board ships. Various means of communication are used to aid, such as marine radio, email, landline, mobile or satellite telephones, or facsimile, when the ship is days or even hours away from the nearest port and at distances that make direct transit impractical or impossible. In Greece, the M.A.C. (Medical Advice Centre) was established in 1987, mainly for merchant ships, fishing vessels, and pleasure craft of all categories, regardless of flag, place of sailing, or nationality. In this paper, an Internet Information System was developed to support recording health incidents at sea, as these are legally required to be recorded in the M.A.C. The system was developed using the Anvil tool and the Python programming language.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"233-237"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813369","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}
引用次数: 0
Open-Source Approach to Disease Surveillance: Designing a Cost-Effective, Scalable Solution.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250130
Rukshan Ranatunge, Palitha Karunapema, Buddhika Ariyaratne
{"title":"Open-Source Approach to Disease Surveillance: Designing a Cost-Effective, Scalable Solution.","authors":"Rukshan Ranatunge, Palitha Karunapema, Buddhika Ariyaratne","doi":"10.3233/SHTI250130","DOIUrl":"https://doi.org/10.3233/SHTI250130","url":null,"abstract":"<p><p>It is challenging for lower and middle income countries to develop health information systems due to resource constraints. Here we show how open source community and open source dynamics were used to develop the National Covid Health Information System for the Ministry of Health Sri Lanka. Leveraging open source community and dynamics led to development and implementation of a mature disease surveillance system with zero budget for the Ministry of Health Sri Lanka at the height of the pandemic, wth user acceptance similar to proprietary solutions.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"449-452"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813374","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}
引用次数: 0
Patient Perceptions of Virtual Reality in Cancer Rehabilitation: A Qualitative Study.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250120
Aileen S Gabriel, Patricia Rocco, C Mahony Reategui-Rivera, Aref Smiley, Jennifer Lloyd, Manish Kohli, Joseph Finkelstein
{"title":"Patient Perceptions of Virtual Reality in Cancer Rehabilitation: A Qualitative Study.","authors":"Aileen S Gabriel, Patricia Rocco, C Mahony Reategui-Rivera, Aref Smiley, Jennifer Lloyd, Manish Kohli, Joseph Finkelstein","doi":"10.3233/SHTI250120","DOIUrl":"https://doi.org/10.3233/SHTI250120","url":null,"abstract":"<p><p>This study investigates the use of virtual reality (VR) for cancer rehabilitation (CR) among patients with metastatic prostate cancer (mPC) undergoing androgen deprivation therapy (ADT). Interviews with 20 participants revealed that the engaging visuals and gamified exercise routines of the VR system enhanced motivation and supported personalized activities. However, some participants encountered challenges, including difficulty using the headset with glasses, initial confusion with technical terms, and concerns about cost and equipment durability. While most appreciated the system's flexibility for home-based rehabilitation, one participant preferred traditional, non-technological exercises. These findings suggest that VR can effectively address barriers in conventional cancer rehabilitation programs, but improvements in user support and cost considerations are necessary for wider acceptance. Further research should focus on the long-term effects of VR on patient outcomes.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"399-403"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813401","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}
引用次数: 0
Predicting Survival in Metastatic Castration-Resistant Prostate Cancer Patients: Development of a Prognostic Nomogram.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250070
Xingyue Huo, Manish Kohli, Joseph Finkelstein
{"title":"Predicting Survival in Metastatic Castration-Resistant Prostate Cancer Patients: Development of a Prognostic Nomogram.","authors":"Xingyue Huo, Manish Kohli, Joseph Finkelstein","doi":"10.3233/SHTI250070","DOIUrl":"https://doi.org/10.3233/SHTI250070","url":null,"abstract":"<p><p>Patients with metastatic castration-resistant prostate cancer (mCRPC) have a 5-year survival rate of approximately 30%. Accurate prediction of survival in these patients is critical for optimal choice of patient treatment. This study aimed to develop a nomogram to accurately predict overall survival in mCRPC patients in routine clinical practice. We developed a nomogram based on a Cox proportional hazards model with predictors including treatment groups, ALP, LDH, albumin, hemoglobin, and PSA. Model performance was evaluated by AUC, calibration curves, and C-index with internal validation via bootstrapping. High ALP, high LDH, high PSA, low Albumin, and low hemoglobin were significantly associated with an increased risk of death. The nomogram showed good predictive accuracy, with a C-index of 0.637 and AUC of 0.736, 0.686, and 0.712 for 1-, 2-, and 3-year survival predictions. Calibration plots showed strong alignment between predicted and observed survival. The nomogram can be successfully used in clinical practice.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"164-168"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143812952","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}
引用次数: 0
Enhancing Survival Prediction: The Potential of Whole-Brain Radiomics in Multimodal Neuroimaging.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250068
Gleb Danilov, Diana Kalaeva, Nina Vikhrova, Svetlana Shugay, Ekaterina Telysheva, Sergey Goraynov, Alexandra Kosyrkova, Galina Pavlova, Sergey Drozd, Nadezhda Samoylenkova, Igor Pronin, Dmitriy Usachev
{"title":"Enhancing Survival Prediction: The Potential of Whole-Brain Radiomics in Multimodal Neuroimaging.","authors":"Gleb Danilov, Diana Kalaeva, Nina Vikhrova, Svetlana Shugay, Ekaterina Telysheva, Sergey Goraynov, Alexandra Kosyrkova, Galina Pavlova, Sergey Drozd, Nadezhda Samoylenkova, Igor Pronin, Dmitriy Usachev","doi":"10.3233/SHTI250068","DOIUrl":"https://doi.org/10.3233/SHTI250068","url":null,"abstract":"<p><p>Radiomics shows promise in enhancing predictions of overall survival (OS) and progression-free survival (PFS) in patients with glial brain tumors. The prognostic significance of imaging biomarkers derived from a whole-brain mask is still unclear. This study aimed to evaluate the potential of radiomics for predictive modeling of OS and PFS in patients with brain gliomas. We compared 13 prognostic models designed to predict OS and PFS, using clinical features alone, radiological biomarkers alone, and a combination of both. Our approach achieved C-index values of 0.900 for OS and 0.903 for PFS. Models built solely on imaging biomarkers exhibited the highest quality, whereas those based only on clinical signs showed the lowest quality. Given the limited data, it is unclear how reproducible the whole-brain radiomic features and corresponding models will be with new data. Nonetheless, there are reasons to view whole-brain radiomics as a promising avenue for further research.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"154-158"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813313","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}
引用次数: 0
Applying Data Mining to Predict Perceived Benefits Risks of Robotics at Home for Dementia Caregiving Among African American Families.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250049
Sunmoo Yoon, Frederick Sun, Melissa Patterson, Robert Crupi, Peter Broadwell, Tess Pottinger, Milea Kim, Nicole Davis
{"title":"Applying Data Mining to Predict Perceived Benefits Risks of Robotics at Home for Dementia Caregiving Among African American Families.","authors":"Sunmoo Yoon, Frederick Sun, Melissa Patterson, Robert Crupi, Peter Broadwell, Tess Pottinger, Milea Kim, Nicole Davis","doi":"10.3233/SHTI250049","DOIUrl":"https://doi.org/10.3233/SHTI250049","url":null,"abstract":"<p><p>We used data mining to predict the attitudes of 527 caregivers towards the pros and cons of using robotics and artificial intelligence (AI) for dementia care in African American families, with a focus on family-level factors. African American family caregivers would prefer using AI home attendant for caregiving, even though there are associated costs, and see the benefits of using AI robots to improve family dynamics, despite the need for the AI to collect sensitive data. In contrast, white family caregivers aged 25-34 are more likely to perceive the risks of using AI robots for this purpose. The proposed AI smart home system evaluates care quality and assists families in nursing home decisions. However, specific groups are hesitant to embrace its benefits. This highlights the need for in-depth research to address concerns and communicate potential advantages effectively.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"61-65"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813326","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}
引用次数: 0
Preliminary Results on Improved Synthetic Image Generation for Melanoma Skin Cancer.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250081
Saadullah Farooq Abbasi, Muhammad Bilal, Teesta Mukherjee, Saif Ul Islam, Omid Pournik, Theodoros N Arvanitis
{"title":"Preliminary Results on Improved Synthetic Image Generation for Melanoma Skin Cancer.","authors":"Saadullah Farooq Abbasi, Muhammad Bilal, Teesta Mukherjee, Saif Ul Islam, Omid Pournik, Theodoros N Arvanitis","doi":"10.3233/SHTI250081","DOIUrl":"https://doi.org/10.3233/SHTI250081","url":null,"abstract":"<p><p>Advances in computer vision have shown interesting results in synthetic image generation. Diffusion models have shown promising outputs while generating realistic images from textual inputs like stable diffusion and Imagen. However, their use in high-quality medical images is limited. Synthetic medical images may play an essential role in privacy-preserved artificial intelligence. In addition, these are also useful for augmenting small datasets. For this reason, this study proposed a stable diffusion-based algorithm for 3-dimensional (3D) skin cancer image generation. The target class in the proposed study is melanoma skin cancer. A lightweight low-rank adaptation technique (LoRA) has been used for training. The proposed approach can efficiently generate 3D images of size 512*512*3. The results have been compared with existing studies to validate the efficacy of the proposed study.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"216-220"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813003","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}
引用次数: 0
Challenges of Artificial Intelligence in Medicine.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250039
Bakheet Aldosari, Hanan Aldosari, Abdullah Alanazi
{"title":"Challenges of Artificial Intelligence in Medicine.","authors":"Bakheet Aldosari, Hanan Aldosari, Abdullah Alanazi","doi":"10.3233/SHTI250039","DOIUrl":"https://doi.org/10.3233/SHTI250039","url":null,"abstract":"<p><p>Artificial Intelligence (AI) holds great promise for healthcare, promising improved patient outcomes and streamlining processes. Nevertheless, this transformational journey comes with numerous potential pitfalls that warrant attention. This comprehensive review explores some key challenges involved with integrating AI into medicine. First and foremost is the risk of over-reliance on AI systems. Users often rely on recommendations provided by AI to follow without question, potentially causing automation bias. Human oversight is essential to avoid mistakes and patient harm; failure to provide such oversight could have serious repercussions that necessitate having someone in control at all times - emphasizing the necessity for having a human-in-the-loop approach. Ethical considerations must always come first when developing AI systems, with privacy, informed consent, and data protection as non-negotiable obligations for patients and organizations. Transparency and accountability within AI systems are necessary to quickly identify biases or errors to enable AI development with integrity that mitigates bias, ensures fairness, and maintains transparency. Ethical AI development involves ongoing efforts made with great diligence by developers to mitigate any bias, ensure fairness, and maintain transparency. These principles form the bedrock upon which ethical development depends. Collaboration between healthcare providers and AI developers is of utmost importance for patient safety and well-being; healthcare providers must protect patient data while developers must ensure AI systems adhere to legal and ethical requirements. AI and healthcare present significant challenges. Ethical frameworks, bias mitigation techniques, and transparency measures must all be pursued to advance AI's role within healthcare delivery systems. We can unleash AI's full potential by overcoming such hurdles while upholding patient safety, ethics, and quality care as the cornerstones of healthcare innovation.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"16-20"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813022","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}
引用次数: 0
Comparing Emotional Valence from Human Quantitative Ratings and Qualitative Narrative Data on Using Artificial Intelligence to Reduce Caregiving Disparity.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250036
Sunmoo Yoon, Robert Crupi, Frederick Sun, Dante Tipiani, Melissa Patterson, Tess Pottinger, Milea Kim, Ncole Davis
{"title":"Comparing Emotional Valence from Human Quantitative Ratings and Qualitative Narrative Data on Using Artificial Intelligence to Reduce Caregiving Disparity.","authors":"Sunmoo Yoon, Robert Crupi, Frederick Sun, Dante Tipiani, Melissa Patterson, Tess Pottinger, Milea Kim, Ncole Davis","doi":"10.3233/SHTI250036","DOIUrl":"https://doi.org/10.3233/SHTI250036","url":null,"abstract":"<p><p>We compared emotional valence scores as determined via machine vs human ratings from a survey conducted from April to May 2024 on perceived attitudes on the use of artificial intelligence (AI) for African American family caregivers of persons with Alzheimer's disease and related dementias (ADRD) (N=627). The participants answered risks, benefits and possible solutions qualitatively on the open-ended questions on ten AI use cases, followed by a rating of each. Then, we applied three machine learning algorithms to detect emotional valence scores from the text data and compared their mean to the human ratings. The mean emotional valence scores from text data via natural language processing (NLP) were negative regardless of algorithms (AFINN: -1.61 ± 2.76, Bing: -1.40 ± 1.52, and Syuzhet: -0.67 ± 1.14), while the mean score of human ratings was positive (2.30 ± 1.48, p=0.0001). Our findings have implications for the practice of survey design using self-rated instruments and open-ended questions in an NLP era.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813030","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}
引用次数: 0
Extracting Regions of Interest and Selective Feature Application in Leukaemia Image Classification.
Studies in health technology and informatics Pub Date : 2025-04-08 DOI: 10.3233/SHTI250058
Marinela Branescu, Stephen Swift, Allan Tucker, Steve Counsell
{"title":"Extracting Regions of Interest and Selective Feature Application in Leukaemia Image Classification.","authors":"Marinela Branescu, Stephen Swift, Allan Tucker, Steve Counsell","doi":"10.3233/SHTI250058","DOIUrl":"https://doi.org/10.3233/SHTI250058","url":null,"abstract":"<p><p>Evaluating the blood smear test images remains the main route of detecting the type of leukaemia, accurate diagnosis is fundamental in providing effective treatment. The changes in the structure of the white blood cells present different morphological characteristics translated into extractable features. This paper explores techniques for manipulating a reduced dataset to increase the classification with CNN (Convolutional neural Network) and feature extraction. Extracting ROI (Regions of Interest) divides the leukaemia images into points of interest respective white blood cells, expanding the dataset an important factor for CNN's performance. Segmenting the initial dataset into ROI through computation after applying Otsu thresholding results in a new dataset of images. The two datasets are analysed, feature extraction performs better on the initial dataset while CNN's accuracy is higher for ROI images. Further steps will divide the images into filtered regions of interest where more specific characteristics are extracted to increase the accuracy.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"323 ","pages":"106-110"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813350","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}
引用次数: 0
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