Healthcare Technology Letters最新文献

{"title":"Open your black box classifier","authors":"Paulo Jorge Gomes Lisboa","doi":"10.1049/htl2.12050","DOIUrl":"10.1049/htl2.12050","url":null,"abstract":"<p>A priority for machine learning in healthcare and other high stakes applications is to enable end-users to easily interpret individual predictions. This opinion piece outlines recent developments in interpretable classifiers and methods to open black box models.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"11 4","pages":"210-212"},"PeriodicalIF":2.8,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11294928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42635295","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":"Secure medical image transmission using deep neural network in e-health applications","authors":"Ala Abdulsalam Alarood,&nbsp;Muhammad Faheem,&nbsp;Mahmoud Ahmad Al-Khasawneh,&nbsp;Abdullah I. A. Alzahrani,&nbsp;Abdulrahman A. Alshdadi","doi":"10.1049/htl2.12049","DOIUrl":"10.1049/htl2.12049","url":null,"abstract":"<p>Recently, medical technologies have developed, and the diagnosis of diseases through medical images has become very important. Medical images often pass through the branches of the network from one end to the other. Hence, high-level security is required. Problems arise due to unauthorized use of data in the image. One of the methods used to secure data in the image is encryption, which is one of the most effective techniques in this field. Confusion and diffusion are the two main steps addressed here. The contribution here is the adaptation of the deep neural network by the weight that has the highest impact on the output, whether it is an intermediate output or a semi-final output in additional to a chaotic system that is not detectable using deep neural network algorithm. The colour and grayscale images were used in the proposed method by dividing the images according to the Region of Interest by the deep neural network algorithm. The algorithm was then used to generate random numbers to randomly create a chaotic system based on the replacement of columns and rows, and randomly distribute the pixels on the designated area. The proposed algorithm evaluated in several ways, and compared with the existing methods to prove the worth of the proposed method.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 4","pages":"87-98"},"PeriodicalIF":2.1,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/htl2.12049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10354750","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":"Assessment of human gait after total knee arthroplasty by dynamic time warping algorithm","authors":"Reza Abbasi-Kesbi,&nbsp;Mohammad Fathi,&nbsp;Mohammad Najafi,&nbsp;Alireza Nikfarjam","doi":"10.1049/htl2.12047","DOIUrl":"10.1049/htl2.12047","url":null,"abstract":"<p>Today, the elderly population is increasing, and there are many drawbacks for them, especially defects in their knee joints which lead to improper gait. To solve this problem, their knee joint can be replaced with knee arthroplasty. In this letter, level of improvement in the human gait before and after total knee arthroplasty (TKA) surgery is investigated using the dynamic time warping (DTW) algorithm. For this purpose, several volunteers who have problems with their knees are incorporated in a test before and after TKA surgery. Then, the data of gait analysis is collected and the data is compared with a reference using the DTW algorithm. The outcome results illustrate an improvement of 89%–97% by the proposed algorithm after TKA surgery. Therefore, patients can see improvement with high accuracy and very fast that result in more use this technique in TKR surgery.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 4","pages":"73-79"},"PeriodicalIF":2.1,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/htl2.12047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9926733","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":"Non-invasive ventilation treatment for patients with chronic obstructive pulmonary disease","authors":"Fleur T. Tehrani,&nbsp;James H. Roum","doi":"10.1049/htl2.12048","DOIUrl":"10.1049/htl2.12048","url":null,"abstract":"<p>Chronic obstructive pulmonary disease (COPD) affects the lives of millions of patients worldwide. Patients with advanced COPD may require non-invasive ventilation (NIV) to support the resultant deficiencies of the respiratory system. The purpose of this study was to evaluate the effects of varying the continuous positive airway pressure (CPAP) and oxygen supplementation components of NIV on simulated COPD patients by using an established and detailed model of the human respiratory system. The model used in the study simulates features of advanced COPD including the effects on the changes in ventilation control, increases in respiratory dead space and airway resistance, and the acid–base shifts in the blood seen in these patients over time. The results of the study have been compared with and found to be in general agreement with available clinical data. Our results demonstrate that under non-emergency conditions, low levels of oxygen supplementation combined with low levels of CPAP therapy seem to improve hypoxemia and hypercapnia in the model, whereas prolonged high-level CPAP and moderate-to-high levels of oxygen supplementation do not. The authors conclude that such modelling may be useful to help guide beneficial interventions for COPD patients using NIV.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 4","pages":"80-86"},"PeriodicalIF":2.1,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/htl2.12048","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9926735","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":"Feasibility study of a clinical decision support system for polymedicated patients in primary care","authors":"Juan Manuel Pinar Manzanet,&nbsp;Giuseppe Fico,&nbsp;Beatriz Merino-Barbancho,&nbsp;Liss Hernández,&nbsp;Cecilia Vera-Muñoz,&nbsp;Germán Seara,&nbsp;Macarena Torrego,&nbsp;Henar Gonzalez,&nbsp;Jonas Wastesson,&nbsp;Johan Fastbom,&nbsp;Julio Mayol,&nbsp;Kristina Johnell,&nbsp;Tomás Gómez-Gascón,&nbsp;María Teresa Arredondo","doi":"10.1049/htl2.12046","DOIUrl":"10.1049/htl2.12046","url":null,"abstract":"<p>Age-related changes in pharmacokinetics and pharmacodynamics, multimorbidity, frailty, and cognitive impairment represent challenges for drug treatments. Moreover, older adults are commonly exposed to polypharmacy, leading to increased risk of drug interactions and related adverse events, and higher costs for the healthcare systems. Thus, the complex task of prescribing medications to older polymedicated patients encourages the use of Clinical Decision Support Systems (CDSS). This paper evaluates the CDSS miniQ for identifying potentially inappropriate prescribing in poly-medicated older adults and assesses the usability and acceptability of the system in health care professionals, patients, and caregivers. The results of the study demonstrate that the miniQ system was useful for Primary Care physicians in significantly improving prescription, thereby reducing potentially inappropriate medication prescriptions for elderly patients. Additionally, the system was found to be beneficial for patients and their caregivers in understanding their medications, as well as usable and acceptable among healthcare professionals, patients, and caregivers, highlighting the potential to improve the prescription process and reduce errors, and enhancing the quality of care for elderly patients with polypharmacy, reducing adverse drug events, and improving medication management.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 3","pages":"62-72"},"PeriodicalIF":2.1,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/65/e0/HTL2-10-62.PMC10230557.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9940020","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":"Automatic cardiac arrhythmias classification using CNN and attention-based RNN network","authors":"Jie Sun","doi":"10.1049/htl2.12045","DOIUrl":"10.1049/htl2.12045","url":null,"abstract":"<p>Cardiac disease has become a severe threat to public health according to the government report. In China, there are 0.29 billion cardiac patients and early diagnosis will greatly reduce mortality and improve life quality. Electrocardiogram (ECG) signal is a priority tool in the diagnosis of heart diseases because it is non-invasive and easily available with a simple diagnostic tool of low cost. The paper proposes an automatic classification model by combing convolutional neural network (CNN) and recurrent neural network (RNN) to distinguish different types of cardiac arrhythmias. Morphology features of the raw ECG signals are extracted by CNN blocks and fed into a bidirectional gated recurrent unit (GRU) network. Attention mechanism is used to highlight specific features of the input sequence and contribute to the performance improvement of classification. The model is evaluated with two datasets considering the class imbalance problem constructed with records from MIT-BIH arrhythmia database and China Physiological Signal Challenge 2018 database. Experimental results show that this model achieves good performance with an average F1 score of 0.9110 on public dataset and 0.9082 on subject-specific dataset, which may have potential practical applications.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 3","pages":"53-61"},"PeriodicalIF":2.1,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9b/ac/HTL2-10-53.PMC10230559.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9923670","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":"Detection and classification of atrial and ventricular cardiovascular diseases to improve the cardiac health literacy for resource constrained regions","authors":"Neha Arora,&nbsp;Biswajit Mishra","doi":"10.1049/htl2.12043","DOIUrl":"10.1049/htl2.12043","url":null,"abstract":"<p>ECG is a non-invasive way of determining cardiac health by measuring the electrical activity of the heart. A novel detection technique for feature points P, QRS and T is investigated to diagnose various atrial and ventricular cardiovascular anomalies with ECG signals for ambulatory monitoring. Before the system is worthy of field trials, it is validated with several databases and recorded their response. The QRS complex detection is based on the Pan Tompkins algorithm and difference operation method that provides positive predictivity, sensitivity and false detection rate of 99.29%, 99.49% and 1.29%, respectively. Proposed novel T wave detection provides sensitivity of 97.78%. Also, proposed P wave detection provides positive predictivity, sensitivity and false detection rate of 99.43%, 99.4% and 1.15% for the control study (normal subjects) and 82.68%, 94.3% and 25.4% for the case (patients with cardiac anomalies) study, respectively. Disease detection such as arrhythmia is based on standard R-R intervals while myocardial infarction is based on the ST-T deviations where the positive predictivity, sensitivity and accuracy are observed to be 94.6%, 84.2% and 85%, respectively. It should be noted that, since the frontal leads are only used, the anterior myocardial infarction cases are detected with the injury pattern in lead <i>avl</i> and ST depression in reciprocal leads. Detection of atrial fibrillation is done for both short and long duration signals using statistical methods using interquartile range and standard deviations, giving very high accuracy, 100% in most cases. The system hardware for obtaining the 2 lead ECG signal is designed using commercially available off the shelf components. Small field validation of the designed system is performed at a Public Health Centre in Gujarat, India with 42 patients (both cases and controls). 78.5% accuracy was achieved during the field validation. It is thus concluded that the proposed method is ideal for improvisation in cardiac health monitoring outreach in resource constrained regions.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 3","pages":"35-52"},"PeriodicalIF":2.1,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/htl2.12043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9923668","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":"On the prediction of premature births in Hispanic labour patients using uterine contractions, heart beat signals and prediction machines","authors":"Ejay Nsugbe,&nbsp;Jose Javier Reyes-Lagos,&nbsp;Dawn Adams,&nbsp;Oluwarotimi Williams Samuel","doi":"10.1049/htl2.12044","DOIUrl":"10.1049/htl2.12044","url":null,"abstract":"<p>Preterm birth is a global epidemic affecting millions of mothers across different ethnicities. The cause of the condition remains unknown but has recognised health-based implications, in addition to financial and economic ones. Machine Learning methods have enabled researchers to combine datasets using uterine contraction signals with various forms of prediction machines to improve awareness of the likelihood of premature births. This work investigates the feasibility of enhancing these prediction methods using physiological signals including uterine contractions, and foetal and maternal heart rate signals, for a population of south American women in active labour. As part of this work, the use of the Linear Series Decomposition Learner (LSDL) was seen to lead to an improvement in the prediction accuracies of all models, which included supervised and unsupervised learning models. The results from the supervised learning models showed high prediction metrics upon the physiological signals being pre-processed by the LSDL for all variations of the physiological signals. The unsupervised learning models showed good metrics for the partitioning of Preterm/Term labour patients from their uterine contraction signals but produced a comparatively lower set of results for the various kinds of heart rate signals investigated.</p>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 1-2","pages":"11-22"},"PeriodicalIF":2.1,"publicationDate":"2023-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/htl2.12044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9378174","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":"Acceptance factors of telemedicine technology during Covid-19 pandemic among health professionals: A qualitative study","authors":"Rouidi Mohammed,&nbsp;Elouadi Abd Elmajid,&nbsp;Hamdoune Amine,&nbsp;Choujtani Khadija","doi":"10.1049/htl2.12042","DOIUrl":"10.1049/htl2.12042","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Health professionals are the main users of telemedicine systems, and their acceptance will contribute to the successful implementation of this technology. The objective of this study is to provide a better understanding of the issues surrounding the acceptance of telemedicine technology by Moroccan health professionals in the public sector, in the preparation for a possible generalization of this technology in Morocco.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>Following a literature review, the authors mobilized a modified version of the unified model of technology acceptance and use, to explain and understand the determinants of health professionals’ intention to accept telemedicine technology. The authors’ methodology is based on a qualitative analysis and is primarily based on data obtained through semi-structured interviews with health professionals, who the authors believe are the primary actors in the acceptance of this technology within Moroccan hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The authors’ results suggest that performance expectancy, effort expectancy, compatibility, facilitating conditions, perceived incentives, and social influence have a significant positive impact on health professionals’ behavioural intention to accept telemedicine technology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Practical implications</h3>\u0000 \u0000 <p>From a practical point of view, the results of this study can help the government, organizations responsible for the implementation of telemedicine, and policymakers to understand the key factors that may affect the behaviour of future users of this technology, and to develop very specific strategies and policies for a successful generalization.</p>\u0000 </section>\u0000 </div>","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"10 1-2","pages":"23-33"},"PeriodicalIF":2.1,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/e6/b7/HTL2-10-23.PMC10107386.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9378173","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":"An integrated approach for mental health assessment using emotion analysis and scales","authors":"N. Shanthi, Albert Alexander Stonier, A. Sherine, T. Devaraju, S. Abinash, R. Ajay, V. Arul Prasath, Vivekananda Ganji","doi":"10.1049/htl2.12040","DOIUrl":"https://doi.org/10.1049/htl2.12040","url":null,"abstract":"","PeriodicalId":37474,"journal":{"name":"Healthcare Technology Letters","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41686657","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}