Readable research linked to original sources
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Browse normalized, publication-ready research with direct links to its evidence and source.
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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
Loading articles data…
Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
6 articles
Newest firstBackgroundThe increasing availability of routinely collected health data offers new opportunities for population-level research, yet access to comprehensive, linked, and standardised datasets remains limited. We describe EST-Health-30, a large-scale, population-representative health data resource from Estonia. MethodsEST-Health-30 comprises a random 30% sample of the Estonian population (~500,000 individuals), wit…
Open article record in new tab ↗BackgroundExperiences of violence are reported frequently by mental health service users, victims of violence are at a greater risk of mental health disorders, and violence may sometimes occur as a consequence of a mental disorder. Electronic health records (EHRs) are an important source of information about healthcare, and its social context. Occurrences of violence are not routinely recorded as structured data i…
Open article record in new tab ↗Abstract Background People living with HIV experience high rates of mental health disorders, but the comorbidity patterns of these conditions remain poorly understood. Identifying how disorders cluster and which diagnoses are most central may guide more effective screening and integrated treatment strategies. Methods This cross-sectional study used electronic health records and survey data from the National Instit…
Open article record in new tab ↗The healthcare landscape is experiencing a transformation with the integration of Artificial Intelligence (AI) into traditional analytic workflows. However, this advancement encounters challenges due to variations in clinical practices, resulting in a crisis of generalisability. Addressing this issue, our proposed solution, EHR-ML, offers an open-source pipeline designed to empower researchers and clinicians. By l…
Open article record in new tab ↗IntroductionThe rapid adoption of electronic health records (EHR) across the globe by the healthcare industry is an indication of the rising digitalization of healthcare functions. Despite the potential benefits of EHR, achieving a fit between physician workflow and EHR has posed a major challenge, with negative effects on physician wellbeing and patient outcomes. To this effect, organizations have attempted to al…
The adoption of electronic health records (EHRs) has created opportunities to analyze historical data for predicting clinical outcomes and improving patient care. However, non-standardized data representations and anomalies pose major challenges to the use of EHRs in digital health research. To address these challenges, we have developed EHR-QC, a tool comprising two modules: the data standardization module and th…
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