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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.
10 articles
Newest firstBackground Machine learning (ML) has growing potential to support early identification of high-risk pregnancies in resource-constrained settings. However, most studies focus on model development and predictive performance, with less attention to the health-system processes required to generate ML-ready data and translate risk information into clinical action. The Mlinde Mama Project in Tanzania combined Group Ante…
Open article record in new tab ↗Early identification of patients with advanced chronic conditions (MACA) remains a critical challenge in clinical practice, often relying on retrospective criteria or clinical judgment, which may delay timely and personalized intervention. The increasing availability of electronic health records (EHR) enables the application of Machine Learning (ML) techniques to support more proactive detection. This study aimed…
BackgroundTwo-thirds of Dutch cardiovascular risk management (CVRM) for patients at risk of cardiovascular disease is delivered in primary care practices. While individual risk scores are increasingly used during consultation, a population-level structure for risk-based patient outreach is not currently available. We therefore developed the PROSPERA programme, a multilevel intervention comprising population-level…
BackgroundChronic kidney disease (CKD) affects approximately 10% of adults in England. <1% progress to end stage-kidney disease (ESKD), significantly impacting health-related quality of life with high healthcare costs. CKD is associated with cardiovascular disease risk. New therapies to improve outcomes highlight the need for effective risk stratification. AimTo explore primary care teams views and experiences of…
BackgroundPrecision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (PCI) remains a clinical challenge. Current risk stratification methods lack personalization, underscoring the need for advanced predictive tools. We developed and validated an artificial intelligence (AI) framework (LightGBM, random forest [RF], logistic regression [LR]) to optimize DAPT duration using mul…
Open article record in new tab ↗Objective To determine accuracy of SAGES, ASGE and ESGE criteria for predicting presence of common bile duct (CBD) stones. Methods In a prospective study at Jinnah Hospital Lahore from March 2021 to February 2022, patients with suspected CBD stone were stratified in High risk (HR), intermediate risk (IR) and low risk (LR) for SAGES, ASGE and ESGE criteria. All patients underwent ERCP and risk strata were analyzed…
Open article record in new tab ↗BackgroundSelf-harm is one of the most common presentations at accident and emergency departments in the UK and is a strong predictor of suicide risk. The UK Government has prioritised identifying risk factors and developing preventative strategies for self-harm. Machine learning offers a potential method to identify complex patterns with predictive value for the risk of self-harm. MethodsNational data in the UK M…
BackgroundRoutine mammography screening is currently the standard tool for finding cancers at an early stage, when treatment is most successful. Current breast screening programmes are one-size-fits-all which all women above a certain age threshold are encouraged to participate. However, breast cancer risk varies by individual. The BREAst screening Tailored for HEr (BREATHE) study aims to assess acceptability of a…
BackgroundQuarantine of healthcare workers (HCWs) exposed to COVID -19 confirmed cases is a well-known strategy for limiting the transmission of infection. However, there is need of evidence-based guidelines for quarantine of HCWs in COVID -19. MethodsWe describe our experience of contact tracing and risk stratification of 3853 HCWs who were exposed to confirmed COVID-19 cases in a tertiary health care institution…
Open article record in new tab ↗The widespread adoption of electronic medical records (EMRs) in healthcare has provided vast new amounts of data for statistical machine learning researchers in their efforts to model and predict patient health status, potentially enabling novel advances in treatment. In the case of sepsis, a debilitating, dysregulated host response to infection, extracting subtle, uncataloged clinical phenotypes from the EMR with…