Distributed adaptive Huber regression
Evaluating the robustness of targeted maximum likelihood estimators via realistic simulations in nutrition intervention ...
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Several recently developed methods have the potential to harness machine learning in the pursuit of target quantities inspired by causal inference, including inverse weighting, doubly robust estimating equations and substitution estimators like targeted maximum likelihood estimation. There are even more recent augmentations of these procedures that...
Best practice in statistics: The use of log transformation.
Published in Annals of clinical biochemistry
The log transformation is often used to reduce skewness of a measurement variable. If, after transformation, the distribution is symmetric, then the Welch t-test might be used to compare groups. If, also, the distribution becomes close to normal, then a reference interval might be determined.
Effectiveness of seminar-case learning for use in practice teaching of statistics for undergraduates majoring in prevent...
Published in BMC medical education
The seminar-case learning (SCL) method is a case-oriented teaching model, with teachers and students as the main body of teaching, characterized by communication, interaction, and mutual inspiration. This study explored the effects of the SCL method versus traditional lecture-based learning (LBL) in the statistics curriculum for undergraduate stude...
Challenges for mathematical epidemiological modelling
International audience
Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development.
...Published in Journal of nuclear medicine : official publication, Society of Nuclear Medicine
The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations on technical best practices for developin...
Few-shot Quality-Diversity Optimization
In the past few years, a considerable amount of research has been dedicated to the exploitation of previous learning experiences and the design of Few-shot and Meta Learning approaches, in problem domains ranging from Computer Vision to Reinforcement Learning based control. A notable exception, where to the best of our knowledge, little to no effor...
Comparing the real-world performance of exponential-family random graph models and latent order logistic models for soci...
Exponential-family random graph models (ERGMs) are widely used in social network analysis when modelling data on the relations between actors. ERGMs are typically interpreted as a snapshot of a network at a given point in time or in a final state. The recently proposed Latent Order Logistic model (LOLOG) directly allows for a latent network formati...
Participation de la République démocratique du Congo au commerce international, analyse des statistiques imports exports...
Nous avons fait une analyse d’exportations et importations de la RDC avec le reste du monde. Par manque de données sur les années récentes, nos observations ont porté sur 4 années (2016-2019). Dans l’objectif d’analyserle solde de la balance commerciale de la RDC, notre question principale a été de savoir : « quelle est la contribution de la RDC da...
Comprehensive RNA dataset of tissue and plasma from patients with esophageal cancer or precursor lesions.
...Published in Scientific data
In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (coding and non...
