Journal of Medical Systems最新文献

Self-Supervised Learning for Near-Wild Cognitive Workload Estimation. 近乎野生认知工作量估算的自我监督学习

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-11-22 DOI: 10.1007/s10916-024-02122-7

Mohammad H Rafiei, Lynne V Gauthier, Hojjat Adeli, Daniel Takabi

{"title":"Self-Supervised Learning for Near-Wild Cognitive Workload Estimation.","authors":"Mohammad H Rafiei, Lynne V Gauthier, Hojjat Adeli, Daniel Takabi","doi":"10.1007/s10916-024-02122-7","DOIUrl":"10.1007/s10916-024-02122-7","url":null,"abstract":"Feedback on cognitive workload may reduce decision-making mistakes. Machine learning-based models can produce feedback from physiological data such as electroencephalography (EEG) and electrocardiography (ECG). Supervised machine learning requires large training data sets that are (1) relevant and decontaminated and (2) carefully labeled for accurate approximation, a costly and tedious procedure. Commercial over-the-counter devices are low-cost resolutions for the real-time collection of physiological modalities. However, they produce significant artifacts when employed outside of laboratory settings, compromising machine learning accuracies. Additionally, the physiological modalities that most successfully machine-approximate cognitive workload in everyday settings are unknown. To address these challenges, a first-ever hybrid implementation of feature selection and self-supervised machine learning techniques is introduced. This model is employed on data collected outside controlled laboratory settings to (1) identify relevant physiological modalities to machine approximate six levels of cognitive-physical workloads from a seven-modality repository and (2) postulate limited labeling experiments and machine approximate mental-physical workloads using self-supervised learning techniques.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"107"},"PeriodicalIF":3.5,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142687257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electronic Health Records Sharing Based on Consortium Blockchain. 基于联盟区块链的电子健康记录共享。

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-11-18 DOI: 10.1007/s10916-024-02120-9

Guangfu Wu, Haiping Wang, Zi Yang, Daojing He, Sammy Chan

{"title":"Electronic Health Records Sharing Based on Consortium Blockchain.","authors":"Guangfu Wu, Haiping Wang, Zi Yang, Daojing He, Sammy Chan","doi":"10.1007/s10916-024-02120-9","DOIUrl":"10.1007/s10916-024-02120-9","url":null,"abstract":"In recent years, Electronic health records (EHR) has gradually become the mainstream in the healthcare field. However, due to the fact that EHR systems are provided by different vendors, data is dispersed and stored, which leads to the phenomenon of data silos, making medical information too fragmented and bringing some challenges to current medical services. Therefore, in view of the difficulties in sharing EHR between medical institutions, the risk of privacy leakage, and the lack of EHR usage control by patients, an EHR sharing model based on consortium blockchain is proposed in this paper. Firstly, the Interplanetary File System is combined with consortium blockchain, which forms a hybrid storage scheme of EHR, this technology effectively improves data security, privacy protection, and operational efficiency. Secondly, the model combines unidirectional multi-hop conditional proxy re-encryption based on type and identity with distributed key generation technology to achieve secure EHR sharing with fine grained control. At the same time, users are required to link the operation records of EHR, so as to realize the traceability of EHR usage. A dynamic Byzantine fault-tolerant algorithm based on reputation and clustering is then proposed to solve the problems of arbitrary master node selection, high latency and low throughput of PBFT, enabling the nodes to reach consensus more efficiently. Finally, the model is analyzed in terms of security and user control, showing that the model is less energy intensive in terms of communication overhead and time consumption, and can effectively achieve secure sharing between medical data.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"106"},"PeriodicalIF":3.5,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large Language Models in Healthcare: An Urgent Call for Ongoing, Rigorous Validation. 医疗保健领域的大型语言模型：紧急呼吁持续、严格的验证。

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-11-16 DOI: 10.1007/s10916-024-02126-3

Gerson Hiroshi Yoshinari Júnior, Luciano Magalhães Vitorino

引用次数: 0

Why Clinicians should Care about YouCare and Other Wearable Health Devices. 为什么临床医生应该关注 YouCare 和其他可穿戴健康设备？

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-11-15 DOI: 10.1007/s10916-024-02123-6

Asif Padiyath, J Nick Pratap, Allan F Simpao

引用次数: 0

A Joint Message from the Outgoing and Incoming Editors-in-Chief. 即将离任和即将上任的主编的联合致辞。

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-11-14 DOI: 10.1007/s10916-024-02124-5

Allan F Simpao, Jesse M Ehrenfeld

引用次数: 0

How Useful are Current Chatbots Regarding Urology Patient Information? Comparison of the Ten Most Popular Chatbots' Responses About Female Urinary Incontinence. 当前有关泌尿科患者信息的聊天机器人有多有用？比较十大最受欢迎聊天机器人关于女性尿失禁的回答。

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-11-13 DOI: 10.1007/s10916-024-02125-4

Arzu Malak, Mehmet Fatih Şahin

{"title":"How Useful are Current Chatbots Regarding Urology Patient Information? Comparison of the Ten Most Popular Chatbots' Responses About Female Urinary Incontinence.","authors":"Arzu Malak, Mehmet Fatih Şahin","doi":"10.1007/s10916-024-02125-4","DOIUrl":"https://doi.org/10.1007/s10916-024-02125-4","url":null,"abstract":"This research evaluates the readability and quality of patient information material about female urinary incontinence (fUI) in ten popular artificial intelligence (AI) supported chatbots. We used the most recent versions of 10 widely-used chatbots, including OpenAI's GPT-4, Claude-3 Sonnet, Grok 1.5, Mistral Large 2, Google Palm 2, Meta's Llama 3, HuggingChat v0.8.4, Microsoft's Copilot, Gemini Advanced, and Perplexity. Prompts were created to generate texts about UI, stress type UI, urge type UI, and mix type UI. The modified Ensuring Quality Information for Patients (EQIP) technique and QUEST (Quality Evaluating Scoring Tool) were used to assess the quality, and the average of 8 well-known readability formulas, which is Average Reading Level Consensus (ARLC), were used to evaluate readability. When comparing the average scores, there were significant differences in the mean mQEIP and QUEST scores across ten chatbots (p = 0.049 and p = 0.018). Gemini received the greatest mean scores for mEQIP and QUEST, whereas Grok had the lowest values. The chatbots exhibited significant differences in mean ARLC, word count, and sentence count (p = 0.047, p = 0.001, and p = 0.001, respectively). For readability, Grok is the easiest to read, while Mistral is highly complex to understand. AI-supported chatbot technology needs to be improved in terms of readability and quality of patient information regarding female UI.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"102"},"PeriodicalIF":3.5,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142621911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Maximising the Quality of Stroke Care: Reporting of Data Collection Methods and Resourcing in National Stroke Registries: A Systematic Review. 最大限度地提高卒中治疗质量：报告国家卒中登记处的数据收集方法和资源配置：系统回顾。

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-10-28 DOI: 10.1007/s10916-024-02119-2

Agnes Jonsson, Nicole Cosgrave, Anna Healy, Lisa Mellon, David J Williams, Anne Hickey

{"title":"Maximising the Quality of Stroke Care: Reporting of Data Collection Methods and Resourcing in National Stroke Registries: A Systematic Review.","authors":"Agnes Jonsson, Nicole Cosgrave, Anna Healy, Lisa Mellon, David J Williams, Anne Hickey","doi":"10.1007/s10916-024-02119-2","DOIUrl":"https://doi.org/10.1007/s10916-024-02119-2","url":null,"abstract":"Stroke registries are tools for improving care and advancing research. We aim to describe the methodology and resourcing of existing national stroke registries. We conducted a systematic search of the published, peer-reviewed literature and grey literature examining descriptions of data collection methods and resourcing of national stroke registries published from 2012 to 2023. The systematic review was registered in PROSPERO (CRD42023393841). 101 records relating to 21 registries in 19 countries were identified. They universally employed web-based platforms for data collection. The principal profession of data collectors was nursing. All included the acute phase of care, 28% (6) registered the pre-hospital (ambulance) phase and 14% (3) included rehabilitation. 80% (17) collected outcome data. The registries varied in their approach to outcome data collection; in 9 registries it was collected by hospitals, in 2 it was collected by the registry, and 7 had linkage to national administrative databases allowing follow-up of a limited number of end points. Coverage of the total number of strokes varies from 6 to 95%. Despite widespread use of Electronic Health Records (EHRs) the ability to automatically populate variables remained limited. Governance and management structures are diverse, making it challenging to compare their resourcing. Data collection for clinical registries requires time and necessary skills and imposes a significant administrative burden on the professionals entering data. We highlight the role of clinical registries as powerful instruments for quality improvement. Future work should involve creating a central repository of stroke registries to enable the development of new registries and facilitate international collaboration.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"100"},"PeriodicalIF":3.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Artificial Intelligent System for Prostate Cancer Diagnosis in Whole Slide Images. 在全切片图像中诊断前列腺癌的人工智能系统

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-10-28 DOI: 10.1007/s10916-024-02118-3

Sajib Saha, Janardhan Vignarajan, Adam Flesch, Patrik Jelinko, Petra Gorog, Eniko Szep, Csaba Toth, Peter Gombas, Tibor Schvarcz, Orsolya Mihaly, Marianna Kapin, Alexandra Zub, Levente Kuthi, Laszlo Tiszlavicz, Tibor Glasz, Shaun Frost

{"title":"An Artificial Intelligent System for Prostate Cancer Diagnosis in Whole Slide Images.","authors":"Sajib Saha, Janardhan Vignarajan, Adam Flesch, Patrik Jelinko, Petra Gorog, Eniko Szep, Csaba Toth, Peter Gombas, Tibor Schvarcz, Orsolya Mihaly, Marianna Kapin, Alexandra Zub, Levente Kuthi, Laszlo Tiszlavicz, Tibor Glasz, Shaun Frost","doi":"10.1007/s10916-024-02118-3","DOIUrl":"10.1007/s10916-024-02118-3","url":null,"abstract":"In recent years a significant demand to develop computer-assisted diagnostic tools to assess prostate cancer using whole slide images has been observed. In this study we develop and validate a machine learning system for cancer assessment, inclusive of detection of perineural invasion and measurement of cancer portion to meet clinical reporting needs. The system analyses the whole slide image in three consecutive stages: tissue detection, classification, and slide level analysis. The whole slide image is divided into smaller regions (patches). The tissue detection stage relies upon traditional machine learning to identify WSI patches containing tissue, which are then further assessed at the classification stage where deep learning algorithms are employed to detect and classify cancer tissue. At the slide level analysis stage, entire slide level information is generated by aggregating all the patch level information of the slide. A total of 2340 haematoxylin and eosin stained slides were used to train and validate the system. A medical team consisting of 11 board certified pathologists with prostatic pathology subspeciality competences working independently in 4 different medical centres performed the annotations. Pixel-level annotation based on an agreed set of 10 annotation terms, determined based on medical relevance and prevalence, was created by the team. The system achieved an accuracy of 99.53% in tissue detection, with sensitivity and specificity respectively of 99.78% and 99.12%. The system achieved an accuracy of 92.80% in classifying tissue terms, with sensitivity and specificity respectively 92.61% and 99.25%, when 5x magnification level was used. For 10x magnification, these values were respectively 91.04%, 90.49%, and 99.07%. For 20x magnification they were 84.71%, 83.95%, 90.13%.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"101"},"PeriodicalIF":3.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11519157/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Assessment of an Inpatient Robotic Nurse Assistant: A Mixed-Method Study. 对住院病人机器人护士助理的评估：一项混合方法研究。

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-10-22 DOI: 10.1007/s10916-024-02117-4

Yee Wei Lim, Shi Wei Tan, Cherylanne Yan Bing Tan, Dong Hee Michael Lee, Wen Ting Siow, Doreen Gek Noi Heng, Amartya Mukhopadhyay, Joo Cheng Lim, Sunil Sivadas, Ee Lin Kimberly Teo, Lawrence Khek Yu Ho, Jason Phua

{"title":"An Assessment of an Inpatient Robotic Nurse Assistant: A Mixed-Method Study.","authors":"Yee Wei Lim, Shi Wei Tan, Cherylanne Yan Bing Tan, Dong Hee Michael Lee, Wen Ting Siow, Doreen Gek Noi Heng, Amartya Mukhopadhyay, Joo Cheng Lim, Sunil Sivadas, Ee Lin Kimberly Teo, Lawrence Khek Yu Ho, Jason Phua","doi":"10.1007/s10916-024-02117-4","DOIUrl":"10.1007/s10916-024-02117-4","url":null,"abstract":"The worldwide nursing shortage has led to the exploration of using robotics to support care delivery and reduce nurses' workload. In this observational, mixed-method study, we examined the implementation of a robotic nurse assistant (RNA) in a hospital ward to support vital signs measurements, medication, and item delivery. Human-robot interaction was assessed in four domains: usability, social acceptance, user experience, and its societal impact. Patients in a general medicine ward were recruited to participate in a one-time trial with the RNA and a post-trial 75-question survey. Patients' interactions with the RNA were video recorded for analysis including patients' behaviours, facial emotions, and visual attention. Focus group discussions with nurses elicited their perceptions of working with the RNA, areas for improvement, and scalability. Sixty-seven patients aged 21-79 participated in the trial. Eight in 10 patients reported positive interactions with the RNA. When the RNA did not perform to expectations, only 25% of patients attributed fault to the RNA. Video analysis showed patients at ease interacting with the RNA despite some technical problems. Nurses saw potential for the RNA taking over routine tasks. However, they were sceptical of real time savings and were concerned with the RNA's ability to work well with older patients. Patients and nurses suggested greater interactivity between RNA and patients. Future studies should examine potential timesaving and whether time saved translated to nurses performing higher value clinical tasks. The utility of improved RNA's social capability in a hospital setting should be explored as well.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"99"},"PeriodicalIF":3.5,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142467807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High Capacity and Reversible Fragile Watermarking Method for Medical Image Authentication and Patient Data Hiding. 用于医学图像认证和病人数据隐藏的高容量可逆脆性水印方法

IF 3.5 3区医学

Journal of Medical Systems Pub Date : 2024-10-19 DOI: 10.1007/s10916-024-02110-x

Riadh Bouarroudj, Fatma Zohra Bellala, Feryel Souami

{"title":"High Capacity and Reversible Fragile Watermarking Method for Medical Image Authentication and Patient Data Hiding.","authors":"Riadh Bouarroudj, Fatma Zohra Bellala, Feryel Souami","doi":"10.1007/s10916-024-02110-x","DOIUrl":"https://doi.org/10.1007/s10916-024-02110-x","url":null,"abstract":"The exchange of medical images and patient data over the internet has attracted considerable attention in the past decade, driven by advancements in communication and health services. However, transferring confidential data through insecure channels, such as the internet, exposes it to potential manipulations and attacks. To ensure the authenticity of medical images while concealing patient data within them, this paper introduces a high-capacity and reversible fragile watermarking model in which an authentication watermark is initially generated from the cover image and merged with the patient's information, photo, and medical report to form the global watermark. This watermark is subsequently encrypted using the chaotic Chen system technique, enhancing the model's security and ensuring patient data confidentiality. The cover image then undergoes a Discrete Fourier Transform (DFT) and the encrypted watermark is inserted into the frequency coefficients using a new embedding technique. The experimental results demonstrate that the proposed method achieves great watermarked image quality, with a PSNR exceeding 113 dB and an SSIM close to 1, while maintaining a high embedding capacity of 3 BPP (Bits Per Pixel) and offering perfect reversibility. Furthermore, the proposed model demonstrates high sensitivity to attacks, successfully detecting tampering in all 18 tested attacks, and achieves nearly perfect watermark extraction accuracy, with a Bit Error Rate (BER) of 0.0004%. This high watermark extraction accuracy is crucial in our situation where patient data need to be retrieved from the watermarked images with almost no alteration.","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"48 1","pages":"98"},"PeriodicalIF":3.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142467808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0