All Outputs (25)

Predictive models in emergency medicine and their missing data strategies: a systematic review (2023)
Journal Article

In the field of emergency medicine (EM), the use of decision support tools based on artificial intelligence has increased markedly in recent years. In some cases, data are omitted deliberately and thus constitute “data not purposely collected” (DNPC)... Read More about Predictive models in emergency medicine and their missing data strategies: a systematic review.

Applications of machine learning methods to assist the diagnosis of autism spectrum disorder (2023)
Book Chapter

Autism spectrum disorder (ASD) is a lifelong neuro-developmental disorder that is generally marked by a set of communication and social impairments. The early diagnosis of autism is genuinely beneficial for the welfare of children and parents as well... Read More about Applications of machine learning methods to assist the diagnosis of autism spectrum disorder.

Use of artificial intelligence to manage patient flow in emergency department during the COVID-19 pandemic: A prospective, single-center study (2022)
Journal Article

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, calculation of the number of emergency department (ED) beds required for patients with vs. without suspected COVID-19 represented a real public health problem. In France, Amiens Pic... Read More about Use of artificial intelligence to manage patient flow in emergency department during the COVID-19 pandemic: A prospective, single-center study.

Computer-aided screening of autism spectrum disorder: Eye-tracking study using data visualization and deep learning (2021)
Journal Article

Background: The early diagnosis of autism spectrum disorder (ASD) is highly desirable but remains a challenging task, which requires a set of cognitive tests and hours of clinical examinations. In addition, variations of such symptoms exist, which ca... Read More about Computer-aided screening of autism spectrum disorder: Eye-tracking study using data visualization and deep learning.

Variational autoencoder for image-based augmentation of eye-tracking data (2021)
Journal Article

Over the past decade, deep learning has achieved unprecedented successes in a diversity of application domains, given large-scale datasets. However, particular domains, such as healthcare, inherently suffer from data paucity and imbalance. Moreover,... Read More about Variational autoencoder for image-based augmentation of eye-tracking data.

Mining the Irish hip fracture database: Learning factors contributing to care outcomes (2020)
Journal Article

Data analytics has opened the door for improving many aspects pertaining to the delivery of healthcare. This study avails of unsupervised machine learning to extract knowledge from the Irish hip fracture database (IHFD). The dataset under considerati... Read More about Mining the Irish hip fracture database: Learning factors contributing to care outcomes.

How can machine learning support the practice of modeling and simulation? —A review and directions for future research
Presentation / Conference Contribution

The use of Machine Learning (ML) has achieved a significant momentum across a very wide range of domains. This paper aims to provide a meeting point for discussing the integration of Modeling and Simulation (M&S) with ML. The discussion presents argu... Read More about How can machine learning support the practice of modeling and simulation? —A review and directions for future research.

ML-Aided simulation: A conceptual framework for integrating simulation models with machine learning
Presentation / Conference Contribution

Recent trends towards data-driven methods may require a substantial rethinking regarding the practice of Modeling &Simulation (M&S). Machine Learning (ML) is now becoming an instrumental artefact for developing new insights, or improving already esta... Read More about ML-Aided simulation: A conceptual framework for integrating simulation models with machine learning.

ScholarBase: Towards a cross-domain knowledgebase for linked scholarly data
Presentation / Conference Contribution

Linked Data has gained a significant momentum over the last years through various initiatives embraced by academia and industry as well. In this paper, we introduce ScholarBase, a research project in progress that is aimed to serve as a Linked Data r... Read More about ScholarBase: Towards a cross-domain knowledgebase for linked scholarly data.

Data-driven patient segmentation using K-means clustering: The case of hip fracture care in Ireland
Presentation / Conference Contribution

Machine learning continues to forge the future of decision making in a broad diversity of domains including healthcare. Data-driven methods are increasingly geared towards leveraging evidence-based insights from large volumes of patient data. In this... Read More about Data-driven patient segmentation using K-means clustering: The case of hip fracture care in Ireland.

Coupling simulation with machine learning: A hybrid approach for elderly discharge planning
Presentation / Conference Contribution

Healthcare systems are increasingly challenged by the phenomenal growth of population ageing. Healthcare executives are, and will be, in an inevitable need of evidence-based artifacts for decision making. The paper addresses issues in the context of... Read More about Coupling simulation with machine learning: A hybrid approach for elderly discharge planning.

Large-scale ontology storage and query using graph database-oriented approach: The case of Freebase
Presentation / Conference Contribution

Ontology has been increasingly recognised as an instrumental artifact to help make sense of large amounts of data. However, the challenges of Big Data significantly overburden the process of ontology storage and query particularly. In this respect, t... Read More about Large-scale ontology storage and query using graph database-oriented approach: The case of Freebase.

Fuzzy-based framework for enterprise resource planning system selection
Presentation / Conference Contribution

The popularity of enterprise resource planning is globally increasing for being the magical word to integrate and automate all areas of business operations. However, many organizations are still having hard times to select the proper ERP package. Sel... Read More about Fuzzy-based framework for enterprise resource planning system selection.

Consistency of XAI models against medical expertise: An assessment protocol
Presentation / Conference Contribution

Despite the significant advances made by Artificial Intelligence (AI) models in enhancing medical diagnostics and prognostics, their opacity poses a hurdle to widespread clinical adoption. In this regard, Explainable AI (XAI) aims to demystify these... Read More about Consistency of XAI models against medical expertise: An assessment protocol.

Explainable NLP model for predicting patient admissions at emergency department using triage notes
Presentation / Conference Contribution

Explainable Artificial Intelligence (XAI) has the potential to revolutionize healthcare by providing more transparent, trustworthy, and understandable predictions made by AI models. To this end, the present study aims to develop an explainable NLP mo... Read More about Explainable NLP model for predicting patient admissions at emergency department using triage notes.

Eye-tracking dataset to support the research on autism spectrum disorder
Presentation / Conference Contribution

The availability of data is a key enabler for researchers across different disciplines. However, domains, such as healthcare, are still fundamentally challenged by the paucity and imbalance of datasets. Health data could be inaccessible due to a vari... Read More about Eye-tracking dataset to support the research on autism spectrum disorder.

Learning embeddings from free-text triage notes using pretrained transformer models
Presentation / Conference Contribution

The advent of transformer models has allowed for tremendous progress in the Natural Language Processing (NLP) domain. Pretrained transformers could successfully deliver the state-of-the-art performance in a myriad of NLP tasks. This study presents an... Read More about Learning embeddings from free-text triage notes using pretrained transformer models.

Vision-based approach for autism diagnosis using transfer learning and eye-tracking
Presentation / Conference Contribution

The potentials of Transfer Learning (TL) have been well-researched in areas such as Computer Vision and Natural Language Processing. This study aims to explore a novel application of TL to detect Autism Spectrum Disorder. We seek to develop an approa... Read More about Vision-based approach for autism diagnosis using transfer learning and eye-tracking.

Multi-channel ConvNet approach to predict the risk of in-hospital mortality for ICU patients
Presentation / Conference Contribution

The healthcare arena has been undergoing impressive transformations thanks to advances in the capacity to capture, store, process, and learn from data. This paper re-visits the problem of predicting the risk of in-hospital mortality based on Time Ser... Read More about Multi-channel ConvNet approach to predict the risk of in-hospital mortality for ICU patients.

Heatmaps for visual explainability of CNN-based predictions for multivariate time series with application to healthcare
Presentation / Conference Contribution

The need for explainable AI is becoming increasingly important for critical decision domains such as healthcare for example. In this context, this paper is concerned with explaining the predictions of Convolutional Neural Networks (CNNs) with particu... Read More about Heatmaps for visual explainability of CNN-based predictions for multivariate time series with application to healthcare.