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Clinical Prediction Models in Epidemiological Studies: Lessons from the Application of QRISK3 to UK Biobank Data Open
Statistical models for clinical risk prediction are often derived using data from primary care databases; however, they are frequently used outside of clinical settings. The use of prediction models in epidemiological studies without exter…
Welcome to the Philosophy of Data Science Section Open
This issue of the Journal of Data Science is the first to feature our new section titled "The Philosophy of Data Science".The aim of this section is to highlight the role of critical scientific reasoning in data science by providing dedica…
Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward Open
Patients in a hospital step-down unit require a level of care that is between that of the intensive care unit (ICU) and that of the general ward. While many patients remain physiologically stabilized, others will suffer clinical emergencie…
Patient-Specific Physiological Monitoring and Prediction Using Structured Gaussian Processes Open
The management of patient well-being can be performed by monitoring continuous time-series vital-sign data via low-cost wearable devices. Automated algorithms may then be used with the resulting data to provide early warning of deteriorati…
The efficacy and effectiveness of machine learning for weaning in mechanically ventilated patients at the intensive care unit: a systematic review Open
Weaning from mechanical ventilation in the intensive care unit (ICU) is a complex clinical problem and relevant for future organ engineering. Prolonged mechanical ventilation (MV) leads to a range of medical complications that increases le…
Recognising Cardiac Abnormalities in Wearable Device Photoplethysmography (PPG) with Deep Learning Open
Cardiac abnormalities affecting heart rate and rhythm are commonly observed in both healthy and acutely unwell people. Although many of these are benign, they can sometimes indicate a serious health risk. ECG monitors are typically used to…
View article: Improving the Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models
Improving the Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models Open
Quantitative systems pharmacology (QSP) models aim to describe mechanistically the pathophysiology of disease and predict the effects of therapies on that disease. For most drug development applications, it is important to predict not only…