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Impact of linkage level on inferences from big data analyses in health and medical research: an empirical study
BackgroundLinkage errors that occur according to linkage levels can adversely affect the accuracy and reliability of analysis results. This study...
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Improve the efficiency and accuracy of ophthalmologists’ clinical decision-making based on AI technology
BackgroundAs global aging intensifies, the prevalence of ocular fundus diseases continues to rise. In China, the tense doctor-patient ratio poses...
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Optimization of vision transformer-based detection of lung diseases from chest X-ray images
BackgroundRecent advances in Vision Transformer (ViT)-based deep learning have significantly improved the accuracy of lung disease prediction from...
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Measuring electronic health literacy in the context of diabetes care: psychometric evaluation of a Persian version of the condition-specific eHealth literacy scale for diabetes
BackgroundThe rise of the internet and social media has led to increased interest among diabetes patients in using technology for information...
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Effect of the data-informed platform for health intervention on the culture of data use for decision-making among district health office staff in North Shewa Zone, Ethiopia: a cluster-randomised controlled trial
BackgroundSimilar to other low and middle-income countries, Ethiopia faces limitations in using local health data for decision-making.We aimed to...
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How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review
BackgroundMedication errors and associated adverse drug events (ADE) are a major cause of morbidity and mortality worldwide. In recent years, the...
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Real-time non-invasive hemoglobin prediction using deep learning-enabled smartphone imaging
BackgroundAccurate measurement of hemoglobin concentration is essential for various medical scenarios, including preoperative evaluations and...
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Design, implementation and usability analysis of patient empowerment in ADLIFE project via patient reported outcome measures and shared decision making
IntroductionThis paper outlines the design, implementation, and usability study results of the patient empowerment process for chronic disease...
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Medical-informed machine learning: integrating prior knowledge into medical decision systems
BackgroundClinical medicine offers a promising arena for applying Machine Learning (ML) models. However, despite numerous studies employing ML in...
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Development and usability testing of an online support tool to identify models and frameworks to inform implementation
BackgroundTheories, models and frameworks (TMFs) are useful when implementing, evaluating and sustaining healthcare evidence-based interventions. Yet...
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Addressing label noise for electronic health records: insights from computer vision for tabular data
The analysis of extensive electronic health records (EHR) datasets often calls for automated solutions, with machine learning (ML) techniques,...
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Operationalizing and digitizing person-centered daily functioning: a case for functionomics
An ever-increasing amount of data on a person’s daily functioning is being collected, which holds information to revolutionize person-centered...
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Establishment of prediction model for mortality risk of pancreatic cancer: a retrospective study
Background and aimPancreatic cancer possesses a high prevalence and mortality rate among other cancers. Despite the low survival rate of this cancer...
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Patterns and factors associated with dental service utilization among insured people: a data mining approach
BackgroundInsurance databases contain valuable information related to the use of dental services. This data is instrumental in decision-making...
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Development of a quantitative index system for evaluating the quality of electronic medical records in disease risk intelligent prediction
ObjectiveThis study aimed to develop and validate a quantitative index system for evaluating the data quality of Electronic Medical Records (EMR) in...
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A tree-based explainable AI model for early detection of Covid-19 using physiological data
With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing...
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Factors associated with the local control of brain metastases: a systematic search and machine learning application
BackgroundEnhancing Local Control (LC) of brain metastases is pivotal for improving overall survival, which makes the prediction of local treatment...
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Using a smartphone-based self-management platform to study sex differences in Parkinson’s disease: multicenter, cross-sectional pilot study
BackgroundPatient-reported outcome (PRO) is a distinct and indispensable dimension of clinical characteristics and recent advances have made remote...
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Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy
IntroductionThe correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for...
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Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis
BackgroundMachine Learning (ML) plays a crucial role in biomedical research. Nevertheless, it still has limitations in data integration and...
