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J.H. Krijthe

38 records found

Background: Despite several randomised controlled trials (RCTs) on the use of adjuvant treatment with corticosteroids in patients with community-acquired pneumonia (CAP), the effect of this intervention on mortality remains controversial. We aimed to evaluate heterogeneity of tre ...
Introduction: Dynamic survival analysis has become an effective approach for predicting time-to-event outcomes based on longitudinal data in neurology, cognitive health, and other health-related domains. With advancements in machine learning, several new methods have been introdu ...
Objective and continuous monitoring of Parkinson’s disease (PD) tremor in free-living conditions could benefit both individual patient care and clinical trials, by overcoming the snapshot nature of clinical assessments. To enable robust detection of tremor in the context of limit ...

Risk-Based Decision Making

Estimands for Sequential Prediction Under Interventions

Prediction models are used among others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an intervention while those at low risk are advised to refrain from it. Standard prediction models do not always ...

Also for k-means

More data does not imply better performance

Arguably, a desirable feature of a learner is that its performance gets better with an increasing amount of training data, at least in expectation. This issue has received renewed attention in recent years and some curious and surprising findings have been reported on. In essence ...
Background: Currently available treatment options for Parkinson's disease are symptomatic and do not alter the course of the disease. Recent studies have raised the possibility that cardiovascular risk management may slow the progression of the disease. Objectives: We estimated t ...

The future of artificial intelligence in intensive care

Moving from predictive to actionable AI

Artificial intelligence (AI) research in the intensive care unit (ICU) mainly focuses on developing models (from linear regression to deep learning) to predict out-
comes, such as mortality or sepsis [1, 2]. However, there is another important aspect of AI that is typically n ...

Causal inference using observational intensive care unit data

A scoping review and recommendations for future practice

This scoping review focuses on the essential role of models for causal inference in shaping actionable artificial intelligence (AI) designed to aid clinicians in decision-making. The objective was to identify and evaluate the reporting quality of studies introducing models for ca ...
Learning curves illustrate how generalization performance of a learner evolves with more training data. While this is a useful tool to characterize learners, not all learning curve behavior is well understood. For instance, it is sometimes assumed that the more training data prov ...

Density of Patient-Sharing Networks

Impact on the Value of Parkinson Care

Background: Optimal care for Parkinson’s disease (PD) requires coordination and collaboration between providers within a complex care network. Individual patients have personalised networks of their own providers, creating a unique informal network of providers who treat (‘share’ ...
Introduction: Unplanned hospital admissions associated with Parkinson's disease could be partly attributable to comorbidities. Methods: We studied nationwide claims databases and registries. Persons with newly diagnosed Parkinson's disease were identified based on the first Parki ...
Background: Timely identification of deteriorating COVID-19 patients is needed to guide changes in clinical management and admission to intensive care units (ICUs). There is significant concern that widely used Early warning scores (EWSs) underestimate illness severity in COVID-1 ...
Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mor ...

ReproducedPapers.org

Openly Teaching and Structuring Machine Learning Reproducibility

We present ReproducedPapers.org : an open online repository for teaching and structuring machine learning reproducibility. We evaluate doing a reproduction project among students and the added value of an online reproduction repository among AI researchers. We use anonymous self- ...
STUDY QUESTION: Do genetic variations in the DNA damage response pathway modify the adverse effect of alkylating agents on ovarian function in female childhood cancer survivors (CCS)? SUMMARY ANSWER: Female CCS carrying a common BR serine/threonine kinase 1 (BRSK1) gene variant a ...
Background: Female childhood cancer survivors (CCSs) carry a risk of therapy-related gonadal dysfunction. Alkylating agents (AA) are well-established risk factors, yet inter-individual variability in ovarian function is observed. Polymorphisms in CYP450 enzymes may explain this v ...

Complexe neurologische aandoeningen in de langdurige zorg

Een verkenning van aantallen, patiëntkenmerken en indicaties

Veel patiënten met een complexe neurologische aandoening, zoals de ziekte van Parkinson, multiple sclerose of restverschijnselen van niet-aangeboren hersenletsel, doen vroeg of laat in hun ziekteproces een beroep op de langdurige zorg. Dat deze mensen een andere zorgbehoefte hebb ...
Background: Both patients and physicians may choose to delay initiation of dopamine replacement therapy in Parkinson's disease (PD) for various reasons. We used observational data to estimate the effect of earlier treatment in PD. Observational data offer a valuable source of evi ...