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Artificial intelligence for healthcare in Africa: a scientometric analysis 人工智能在非洲的医疗保健:科学计量分析
Q2 MEDICAL INFORMATICS Pub Date : 2023-11-06 DOI: 10.1007/s12553-023-00786-8
Basile Njei, Ulrick Sidney Kanmounye, Mouhand F. Mohamed, Anim Forjindam, Nkafu Bechem Ndemazie, Adedeji Adenusi, Stella-Maris C. Egboh, Evaristus S. Chukwudike, Joao Filipe G. Monteiro, Tyler M. Berzin, Akwi W. Asombang
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引用次数: 0
Selection of consistent breath biomarkers of abnormal liver function using feature selection: a pilot study 使用特征选择选择肝功能异常的一致呼吸生物标志物:一项初步研究
Q2 MEDICAL INFORMATICS Pub Date : 2023-11-06 DOI: 10.1007/s12553-023-00787-7
Rakesh Kumar Patnaik, Yu-Chen Lin, Ming Chih Ho, J. Andrew Yeh
Abstract Purpose Breath profiling has gained importance in recent years as it is a non-invasive technique to identify biomarkers for various diseases. Breath profiling of abnormal liver function in individuals for identifying potential biomarkers in exhaled breath could be a useful diagnostic tool. The objective of this study was to identify potential biomarkers in exhaled breath that remain stable and consistent during different physiological states, including rest and brief workouts, intending to develop a non-invasive diagnostic tool for detecting abnormal liver function. Method Our study employed a gas chromatography and mass-spectrometer quantified dataset for analysis. Machine learning techniques, including feature selection and model training, were used to rank and evaluate potential biomarkers' contributions to the model's performance. Statistical methods were applied to filter significant and consistent biomarkers. The final selected biomarkers were iterated for all possible combinations using machine learning algorithms to determine their accuracy range. Furthermore, classification models were used to evaluate the performance metrics of the biomarkers and compare models. Result The final selected biomarkers, including 2-Myristynoyl Pantetheine, Pterin-6 Carboxylic Acid, Methyl Mercaptan, N-Acetyl Cysteine, and Butyric Acid, exhibited stable levels in exhaled breath during different physiological states. They showed high accuracy and precision in detecting abnormal liver function. Our machine learning models achieved an accuracy rate ranging from 0.7 to 0.95 in all conditions, with precision, recall, prediction probability, and a 95% confidence interval ranging from 0.84 to 0.94, using various combinations of these biomarkers. Conclusion Our statistical and machine learning analysis identified significant and potential biomarkers that contribute to the detection of abnormal liver function. These biomarkers were consistent across different physiological states of the body in both patient and healthy groups. The use of breath samples and feature selection machine learning methods proved to be an accurate and reliable approach for identifying these biomarkers. Our findings provide valuable insights for future research in this field and can inform the development of non-invasive and cost-effective diagnostic tests for liver disease.
摘要目的近年来,呼吸谱分析作为一种非侵入性技术来识别各种疾病的生物标志物已经变得越来越重要。对个体异常肝功能进行呼吸谱分析,以识别呼出气体中的潜在生物标志物,可能是一种有用的诊断工具。本研究的目的是确定在不同生理状态下(包括休息和短暂锻炼)呼气中保持稳定和一致的潜在生物标志物,旨在开发一种检测肝功能异常的非侵入性诊断工具。方法采用气相色谱和质谱仪定量数据集进行分析。使用机器学习技术,包括特征选择和模型训练,对潜在生物标志物对模型性能的贡献进行排名和评估。采用统计学方法筛选具有显著性和一致性的生物标志物。最后选择的生物标志物使用机器学习算法迭代所有可能的组合,以确定其准确性范围。此外,使用分类模型来评估生物标志物的性能指标并比较模型。结果最终选择的生物标志物包括2-肉豆油酰基Pantetheine、Pterin-6 Carboxylic Acid、Methyl Mercaptan、N-Acetyl半胱氨酸和Butyric Acid,在不同的生理状态下呼出的气体中具有稳定的水平。检测肝功能异常具有较高的准确性和精密度。我们的机器学习模型在所有条件下的准确率范围为0.7至0.95,精度,召回率,预测概率和95%置信区间范围为0.84至0.94,使用这些生物标志物的各种组合。我们的统计和机器学习分析确定了有助于检测肝功能异常的重要和潜在的生物标志物。这些生物标志物在患者和健康组的身体不同生理状态中是一致的。使用呼吸样本和特征选择机器学习方法被证明是识别这些生物标志物的准确可靠的方法。我们的发现为该领域的未来研究提供了有价值的见解,并可以为肝病的非侵入性和成本效益诊断测试的发展提供信息。
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引用次数: 0
Radiotherapy infrastructure for brain metastasis treatment in Africa: practical guildelines for implementation of a stereotactic radiosurgery (SRS) program 非洲脑转移瘤放射治疗基础设施:实施立体定向放射外科 (SRS) 计划的实用指南
IF 2.5 Q2 MEDICAL INFORMATICS Pub Date : 2023-11-01 DOI: 10.1007/s12553-023-00799-3
Emmanuel Fiagbedzi, Francis Hasford, S. Tagoe, Andrew Nisbet
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引用次数: 0
Significance of Digital Health Technologies (DHTs) to manage communicable and non-communicable diseases in Low and Middle-Income Countries (LMICs) 数字卫生技术(DHT)对中低收入国家(LMICs)管理传染性和非传染性疾病的意义
IF 2.5 Q2 MEDICAL INFORMATICS Pub Date : 2023-11-01 DOI: 10.1007/s12553-023-00792-w
Muhammad Aizaz, Faisal Khan, Babar Ali, Shahbaz Ahmad, Khansa Naseem, Smriti Mishra, Farrakh Ali Abbas, Guiwen Yang
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引用次数: 0
Direct digital radiography: Exploring applications, misuse, and training needs in medical imaging 直接数字放射摄影:探索医学影像的应用、滥用和培训需求
IF 2.5 Q2 MEDICAL INFORMATICS Pub Date : 2023-11-01 DOI: 10.1007/s12553-023-00791-x
M. Abuzaid, W. Elshami, Ali Abdelrazig, Sonyia McFadden
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引用次数: 0
FAIR sharing of health data: a systematic review of applicable solutions 公平共享健康数据:对适用解决方案的系统审查
IF 2.5 Q2 MEDICAL INFORMATICS Pub Date : 2023-11-01 DOI: 10.1007/s12553-023-00789-5
Paul Guillot, M. Bøgsted, C. Vesteghem
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引用次数: 0
Factors influencing medical imaging technology uptake by private hospitals 影响民营医院医学影像技术应用的因素
Q2 MEDICAL INFORMATICS Pub Date : 2023-10-31 DOI: 10.1007/s12553-023-00774-y
Francisco Reyes-Santias, Octavio Cordova-Arevalo, Ivan Busto Dominguez, Manel Antelo
Abstract Purpose This article analyses the factors influencing the uptake of computed tomography (CT) and magnetic resonance imaging (MRI) technologies by a sample of private hospitals located in Galicia-North of Portugal European Region. Methods Regarding adoption, associations with the different variables were analysed by means of binary logistic regression for CT and MRI of data from 24 private hospitals for the period 2006–2019. The sample data used to perform the regression analyses were panel data (Wooldridge in Econometric Analysis of Cross Section and Panel Data, Cambridge, Massachusetts, 1) and statistical significance was established at p ≤ 0.05. Results We find that hospital size, proxied by the number of beds, best explains the decision to adopt CT technology, while the only sociodemographic variable that affects the adoption decision is age above 64 years. Hospital size is also the main explanatory variable for MRI technology adoption, and in this case, all sociodemographic variables, except for population density, affect the adoption decision. Conclusions The availability of a CT scanner reduces the probability of a private hospital adopting MRI technology. Contracts with Public Sector have a counterfactual effect on CT uptake and a negative influence on MRI uptake.
摘要目的分析影响葡萄牙北部加利西亚地区私立医院CT和MRI技术应用的因素。方法对2006-2019年24家民营医院的CT和MRI数据进行二元logistic回归分析,分析采用率与不同变量的相关性。进行回归分析的样本数据为面板数据(Wooldridge in Econometric Analysis of Cross Section and panel data, Cambridge, Massachusetts, 1), p≤0.05具有统计学显著性。结果我们发现医院规模(以床位数量为代表)最能解释采用CT技术的决定,而影响采用决策的唯一社会人口变量是64岁以上的年龄。医院规模也是MRI技术采用的主要解释变量,在这种情况下,除人口密度外,所有社会人口统计学变量都会影响采用决策。结论CT扫描仪的可用性降低了私立医院采用MRI技术的可能性。与公共部门的合同对CT吸收有反事实效应,对MRI吸收有负面影响。
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引用次数: 0
Trimodality image registration of ultrasound, cardiac computed tomography, and magnetic resonance imaging for transcatheter aortic valve implantation and replacement image guidance 超声、心脏计算机断层扫描和磁共振成像的三模态图像配准用于经导管主动脉瓣植入和置换术的图像引导
Q2 MEDICAL INFORMATICS Pub Date : 2023-10-23 DOI: 10.1007/s12553-023-00785-9
Aisyah Rahimi, Azira Khalil, Shahrina Ismail, Aminatul Saadiah Abdul Jamil, Muhammad Mokhzaini Azizan, Khin Wee Lai, Amir Faisal
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引用次数: 0
Automatic detection of breast masses using deep learning with YOLO approach 基于YOLO方法的深度学习乳腺肿块自动检测
Q2 MEDICAL INFORMATICS Pub Date : 2023-10-16 DOI: 10.1007/s12553-023-00783-x
Alejandro Ernesto Quiñones-Espín, Marlen Perez-Diaz, Rafaela Mayelín Espín-Coto, Deijany Rodriguez-Linares, José Daniel Lopez-Cabrera
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引用次数: 0
Ways public health users interact with online health information: a qualitative study 公共卫生用户与在线卫生信息互动的方式:一项定性研究
Q2 MEDICAL INFORMATICS Pub Date : 2023-10-05 DOI: 10.1007/s12553-023-00784-w
Lívia G Fernandes, Karime A Mescouto, Leonardo O P Costa, Bruno Tirotti Saragiotto
Abstract Purpose The use of internet for health-related purposes has increased in the past years; however, the overabundance of information led the world to a health “infodemic”. Little is known about the ways public health users seek health information online and how it influences the relationship between patients and healthcare practitioners. We aimed to investigate how public health users seek health information online and how this practice affects health encounters. Methods We conducted a qualitative study in a public secondary level healthcare facility. Thirty participants were interviewed using a semi-structured grid designed upon the definition of digital health literacy. Participants were mostly women with an average age of 50 years old and educational level equal to or lower than high school degree. Traditionally and digitally illiterate participants participated in the study. Data analysis was performed using a reflexive thematic analysis underpinned by critical theory. Results We identified three interrelated themes: (1) failing to be a digitally engaged patient, (2) health information on the internet resonates better with individuals’ literacy, and (3) vulnerability is welcomed on the internet. Themes explored power dynamics that appeared to be mediated by formal knowledge, sociocultural contexts, use of technical language, and the presence of emotional and affective domains. Conclusion Our findings suggest that health information online might facilitate the understanding of technical terms and fill an emotional gap often overlooked by healthcare practitioners. Findings may assist health professionals in developing ways of considering health information online as part of the health encounter.
在过去的几年里,与健康相关的互联网使用有所增加;然而,信息的过剩导致世界出现了卫生“信息大流行”。关于公共卫生用户在线寻求健康信息的方式以及它如何影响患者和医疗保健从业人员之间的关系,人们知之甚少。我们的目的是调查公共卫生用户如何在网上寻求健康信息,以及这种做法如何影响健康遭遇。方法对某公立二级医疗机构进行定性研究。使用根据数字健康素养定义设计的半结构化网格对30名参与者进行了访谈。参与者大多是平均年龄50岁,教育程度等于或低于高中的女性。传统和数字文盲参与了这项研究。数据分析采用了以批判理论为基础的反身性主题分析。结果:我们确定了三个相互关联的主题:(1)未能成为数字参与的患者,(2)互联网上的健康信息与个人的素养更能产生共鸣,(3)脆弱性在互联网上受到欢迎。主题探讨了权力动态,似乎是由正式知识、社会文化背景、技术语言的使用以及情感和情感领域的存在所介导的。结论网络健康信息可以促进专业术语的理解,填补医护人员经常忽视的情感鸿沟。研究结果可能有助于卫生专业人员制定将在线卫生信息视为健康接触的一部分的方法。
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引用次数: 0
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