Research Insights

This section focusses on the cutting-edge research and findings in the various disciplines of healthcare around the world.

Development and internal validation of prediction models for future hospital care utilization by patients with multimorbidity using electronic health record data

To develop and internally validate prediction models for future hospital care utilization in patients with multiple chronic conditions The prevalence of multimorbidity defined as having two or more chronic conditions is increasing Kingston et al predicted that by of the adults in the UK aged over years will be living with multimorbidity An in...

PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning

Metastatic cancer accounts for over of all cancer deaths and evaluations of metastasis potential are vital for minimizing the metastasisassociated mortality and achieving optimal clinical decisionmaking Computational assessment of metastasis potential based on largescale transcriptomic cancer data is challenging because metastasis events are not a...

The new normal: Covid-19 risk perceptions and support for continuing restrictions past vaccinations

I test the possibility that overestimating negative consequences of COVID eg hospitalizations deaths and threats to children will be associated with stronger support the new normal ie continuation of restrictions for an undefined period starting with widespread access to vaccines and completed vaccinations of vulnerable people

Conceptual model of low-cost improvised bubble continuous positive airway pressure device for adults and its potential use in the COVID-19 pandemic

Lowcost improvised continuous positive airway pressure CPAP device is safe and efficacious in neonatal respiratory distress There is a great necessity for similar device in adults and this has been especially made apparent by the recent Coronavirus Disease COVID pandemic which is unmasking the deficiencies of healthcare system

Transfer learning for non-image data in clinical research: A scoping review

Transfer learning is a form of machine learning where a pretrained model trained on a specific task is reused as a starting point and tailored to another task in a different dataset While transfer learning has garnered considerable attention in medical image analysis its use for clinical

An explainable artificial intelligence approach for predicting cardiovascular outcomes using electronic health records

Understanding the conditionallydependent clinical variables that drive cardiovascular health outcomes is a major challenge for precision medicine Here we deploy a recently developed massively scalable comorbidity discovery method called Poisson Binomial based Comorbidity discovery PBC to analyze Electronic Health Records EHRs from the University

Unifying cardiovascular modelling with deep reinforcement learning for uncertainty aware control of sepsis treatment

Sepsis is a potentially lifethreatening inflammatory response to infection or severe tissue damage It has a highly variable clinical course requiring constant monitoring of the patients state to guide the management of intravenous fluids and vasopressors among other interventions Despite decades of research theres still debate among experts on opti...

To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems

Explainability for artificial intelligence AI in medicine is a hotly debated topic Our paper presents a review of the key arguments in favor and against explainability for AIpowered Clinical Decision Support System CDSS applied to a concrete use case namely an AIpowered CDSS currently used in the emergency call setting to identify patients with lif...

Severity and mortality prediction models to triage Indian COVID-19 patients

As the second wave in India mitigates COVID has now infected about million patients countrywide leading to more than thousand people dead As the infections surged the strain on the medical infrastructure in the country became apparent While the country vaccinates its population opening up the economy may lead to an increase in infection rates

Mortality risk prediction of high-sensitivity C-reactive protein in suspected acute coronary syndrome: A cohort study

There is limited evidence on the use of highsensitivity Creactive protein hsCRP as a biomarker for selecting patients for advanced cardiovascular CV therapies in the modern era The prognostic value of mildly elevated hsCRP beyond troponin in a large realworld cohort of unselected patients presenting with suspected acute coronary syndrome

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