Accuracy, Efficiency, and usability of a Semi-Automated SMART on FHIR venous thromboembolism risk assessment App: A randomised crossover simulation study Venous thromboembolism (VTE) is the leading cause of maternal death. Current VTE risk assessment (VTERA) tools often require manual data entry, which …

#IJMI open access paper: SMART on FHIR improved postpartum VTE risk assessment in randomized crossover simulation. Semi-automated app increased accurate risk scores (63%→87%), improved prophylaxis recommendations (79%→91%), reduced time and data entry burden www.sciencedirect.com/science/arti...

This year on Bluesky I wrote 314 posts and 14 replies. I received 486 likes, 39 likes from my most popular post, I love saying "health" & adding weblinks 🔗 posting about healthcare research, new AI models #medsky #ai #ijmi #dcinetwork #mlsky #aisky #aiinhealthcare
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Enhancing information for action: A strategic tool for strengthening public health emergency management systems This paper addresses the importance of timely and robust information systems that underpin emergency response decision-making, as evidenced during the…

In #IJMI - Enhancing information for action: A strategic tool for strengthening public health emergency management systems - Guides states on improving preparedness, response and recovery strategies. www.sciencedirect.com/science/arti...

Public value and digital health: The example of guiding values in the national digital health strategy of France In the WHO European Region, 44 of 53 reporting Member States (MS) have a national digital health strategy (NDHS) or policy. Their formulation is heter…

In #IJMI - Public value and digital health: The example of guiding values in the national digital health strategy of France - Public values can enhance ethical and societal relevance in digital health policy. www.sciencedirect.com/science/arti...

In #IJMI - Human-centred AI for emergency cardiac care: Evaluating RAPIDx AI with PROLIFERATE_AI - PROLIFERATE_AI can continuously optimise AI tools in dynamic clinical environments. www.sciencedirect.com/science/arti...

EHR-ML: A data-driven framework for designing machine learning applications with electronic health records The healthcare landscape is experiencing a transformation with the integration of Artificial Intelligence (AI) into traditional analytic workflows. Ho…

In #IJMI EHR-ML: A data-driven framework for designing machine learning applications with electronic health records - Provides a reproducible and easy to use standardised framework for designing tailored machine learning applications. www.sciencedirect.com/science/arti...

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabiliti…

In #IJMI Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records - REDAPM using structured and unstructured EHR data to predict depression and anxiety onset in T2DM patients. www.sciencedirect.com/science/arti...

Training machine learning models to detect rare inborn errors of metabolism (IEMs) based on GC–MS urinary metabolomics for diseases screening Gas chromatography-mass spectrometry (GC–MS) has been shown to be a potentially efficient metabolic profiling platform in urine analysis. However, the…

Training machine learning models to detect rare inborn errors of metabolism (IEMs) based on GC–MS urinary metabolomics for diseases screening #IJMI www.sciencedirect.com/science/arti...

Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health AI is big and moving fast into healthcare, creating opportunities and risks. However, current approaches to governance focus on high-level principles …

DCI Network Paper in #IJMI
Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health www.sciencedirect.com/science/arti... aim 1. establish an approach tailored for consumer health AI governance; 2. identify key constraints and desirable model characteristics.

Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health AI is big and moving fast into healthcare, creating opportunities and risks. However, current approaches to governance focus on high-level principles …

DCI Network Paper in #IJMI
Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health www.sciencedirect.com/science/arti... aim 1. establish an approach tailored for consumer health AI governance; 2. identify key constraints and desirable model characteristics.

Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health AI is big and moving fast into healthcare, creating opportunities and risks. However, current approaches to governance focus on high-level principles …

DCI Network Paper in #IJMI: Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health www.sciencedirect.com/science/arti... aim 1. establish an approach tailored for consumer health AI governance; 2. identify key constraints and desirable model characteristics.

A scalable approach for critical care data extraction and analysis in an academic medical center Electronic health records are a valuable asset for research, but their use is challenging due to inconsistencies of records, heterogeneous formats and…

In International Journal of Medical Informatics #IJMI - This study introduces a scalable method for EHR data extraction—now fueling over 120 projects since June 2022. Discover how automated cohort selection & data prep advance research www.sciencedirect.com/science/arti...