Mahmoud Elbattah

Mahmoud Elbattah
Université de Picardie Jules Verne | UPJV

About

45
Publications
22,079
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253
Citations

Publications

Publications (45)
Conference Paper
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 discharge planning for elderly patients with application to hip fracture care in Ireland. A hybrid a...
Article
Full-text available
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 Picardy University Hospital (APUH) developed an Artificial Intelligence (AI) project called "Predictio...
Conference Paper
Full-text available
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 approach that combines TL and eye-tracking, which is commonly used for analyzing autistic features. The ke...
Conference Paper
Full-text available
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 application of transformers to learn contextual embeddings from free-text triage notes, widely reco...
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 can make the identification of ASD even more difficult. Although diagnosis tests are largely developed...
Conference Paper
Data Analytics is rapidly expanding within the healthcare domain to help develop strategies for improving the quality of care and curbing costs as well. Natural Language Processing (NLP) solutions have received particular attention whereas a large part of clinical data is stockpiled into unstructured physician or nursing notes. In this respect, we...
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, datasets could be largely inaccessible due to privacy concerns, or lack of data-sharing incentives....
Preprint
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 can make the identification of ASD even more difficult. Although diagnosis tests are largely developed...
Conference Paper
Full-text available
The implementation of Data Analytics has achieved a significant momentum across a very wide range of domains. Part of that progress is directly linked to the implementation of Text Analytics solutions. Organisations increasingly seek to harness the power of Text Analytics to automate the process of gleaning insights from unstructured textual data....
Conference Paper
Overcrowding in Emergency Departments (ED) is considered as an international issue, which could have adverse impacts on multiple care outcomes such as the length of stay for example. Part of the solution could lie in the early prediction of the patient outcome as discharge or hospitalization. This study applies Deep Learning to this end. A large-sc...
Conference Paper
Autism Spectrum Disorder (ASD) is a lifelong condition generally characterized by social and communication impairments. The early diagnosis of ASD is highly desirable, yet it could be complicated by several factors. Standard tests typically require intensive efforts and experience, which calls for developing assistive tools. In this respect, this s...
Conference Paper
Full-text available
This study explores a Machine Learning-based approach for generating synthetic eye-tracking data. In this respect, a novel application of Recurrent Neural Networks is experimented. Our approach is based on learning the sequence patterns of eye-tracking data. The key idea is to represent eye-tracking records as textual strings, which describe the se...
Conference Paper
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 particular focus on multivariate Time Series (TS) problems. The approach is based on heatmaps as a visual m...
Conference Paper
Full-text available
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 Series (TS) records emanating from ICU monitoring devices. The problem basically represents an applicat...
Article
Full-text available
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 consideration contained patient records over three years 2013–2015. The process of knowledge discovery included...
Conference Paper
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 arguments in favour of why and how the M&S practice can avail of ML in different modalities. In this con...
Conference Paper
Autism spectrum disorder (ASD) is a lifelong condition characterized by social and communication impairments. This study attempts to apply unsupervised Machine Learning to discover clusters in ASD. The key idea is to learn clusters based on the visual representation of eye-tracking scanpaths. The clustering model was trained using compressed repres...
Conference Paper
Full-text available
Autism spectrum disorder (ASD) is a lifelong condition generally characterized by social and communication impairments. The early diagnosis of ASD is highly desirable, and there is a need for developing assistive tools to support the diagnosis process in this regard. This paper presents an approach to help with the ASD diagnosis with a particular f...
Conference Paper
The development of care pathways is increasingly becoming an instrumental artefact towards improving the quality of care and cutting costs. This paper presents a framework that incorporates Simulation Modeling along with Machine Learning (ML) for the purpose of designing pathways and evaluating the return on investment of implementation. The study...
Conference Paper
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 established knowledge. Reflecting this broad scope, the paper presents a conceptual framework to guide t...
Chapter
Full-text available
Recent trends towards data-driven methods may require a substantial rethinking of the process of developing simulation models. In this respect, the chapter aims to promote a discussion on the opportunities and potential for integrating simulation modeling with Machine Learning (ML) in particular. To provide a practical perspective, a realistic use...
Thesis
Recent trends towards data-driven methods may require a substantial rethinking of the process of developing simulation models. For instance, Machine Learning (ML) has demonstrated great potentials for constructing new knowledge, or improving already established knowledge. Reflecting this trend, the study lends support to the discussion of why and h...
Conference Paper
Full-text available
Machine Learning (ML) has demonstrated great potentials for constructing new knowledge, or improving already established knowledge. Reflecting this trend, the paper lends support to the discussion of why and how should ML support the practice of modeling and simulation? Subsequently, the study goes through a use case in relation to healthcare, whic...
Chapter
Full-text available
The world of Big Data continues to expand, and forge the landscape of data analytics. Datasets are rapidly growing in size and complexity, and there is a pressing need to develop solutions that can harness this deluge of data to produce useful insights. Unsupervised techniques, such as clustering, present as appropriate methods for exploring and su...
Data
The dataset contains more than 21M hierarchical relationships about ≈10M topics extracted from Freebase knowledgebase. The topics span the various categories of Freebase including Science & Technology, Arts & Entertainment, Sports, Society, Products & Services, Transportation, Time & Space, Special Interests, and Commons. The relationships describe...
Conference Paper
Full-text available
Predictive analytics have proved promising capabilities and opportunities to many aspects of healthcare practice. Data-driven insights can provide an important part of the solution for curbing rising costs and improving care quality. The paper implements machine learning techniques in an attempt to support decision making in relation to elderly hea...
Conference Paper
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 context, this paper embraces a mere data-driven approach for the segmentation of patients with appl...
Conference Paper
Full-text available
Faced with the challenge of population ageing, healthcare providers are increasingly in need for evidence-based artefacts to support the decision making process. In this regard, the paper avails of machine learning techniques in a bid to support the elderly care planning with application to hip fracture care in Ireland. Specifically, the inpatient...
Conference Paper
Full-text available
For the foreseeable future, quality improvement of Healthcare Service Systems (HSS) will depend on implementing a health information infrastructure that supports human decision making about protocols, processes, and procedures that work together to support the valuebased paradigm. Based on a recent formalization of pathways-based coordination of ca...
Conference Paper
Full-text available
Population ageing is increasing in a rapid pace worldwide, and especially within developed countries. Extraordinary economic challenges are therefore in prospect with regard to healthcare delivery. In this respect, healthcare executives increasingly need tools that can accurately assess the impacts of the foreseen demographic transition. The paper...
Poster
Full-text available
The practice of simulation modeling has been largely dominated by assumptions based on the modeler’s knowledge and preferences, available information, or other factors, which are generally approximate and embedded within the model’s uncertainty. In this study, we present an approach that aims to assist simulation modeling with data-driven knowledge...
Conference Paper
Full-text available
Visualisation is attaining a growing recognition as a pivotal part of the data analysis process. Visualisation-based solutions are increasingly used to adequately explore and communicate understanding of large-scale datasets. This paper presents a web-based visualisation tool, named FreebaseViz, for visually exploring the schema of Freebase. The vi...
Conference Paper
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, the paper aims to convey considerations in relation to improving the practice of storing or querying...
Conference Paper
Full-text available
Clinical pathways (CPs) have been increasingly recognised as an instrumental evidence-based artifact that can support clinical decision making and care planning. However, research focusing on modeling and simulation of CPs is still sparse, despite significant individual endeavours. Initially, the paper conducts a systematic literature review with t...
Conference Paper
Full-text available
Freebase is intended to be an important component of the Linked Open Data (LOD). The paper presents a graph-driven methodology for the analysis and visualisation of Freebase complex schema. First, the methodology utilises Freebase schema types, "Included Type" relationships and "Instance Count" properties to construct a directed weighted graph sche...
Article
Full-text available
Big Data is a rapidly evolving and maturing field which places significant data storage and processing power at our disposal. To take advantage of this power, we need to create new means of collecting and processing large volumes of data at high speed. Meanwhile, as companies and organizations, such as health services, realize the importance and va...
Article
Full-text available
Freebase can be considered as one of the largest sources in the Linked Open Data (LOD) cloud. The paper adopts a graph-driven approach to analyse and visualise Freebase schema. Firstly, the paper demonstrates the extraction process of Freebase schema through stepwise procedures that maintain the schema structure. Secondly, the extracted types and r...
Conference Paper
Full-text available
Successful supply chains management has become a key factor for enterprises to achieve and maintain their competitive advantage. The increasing complexity and agility of supply chains are sustainably growing challenges. Simulation provides advantages over traditional analytical methods in planning and optimisation of supply chains. This paper prese...
Conference Paper
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. Selection of an ERP system is a crucial decision since implementing ERP is complex, very expensive and...
Data
Presenting a diversity of criteria that can be used to guide the selection of ERP systems. The criteria covers seven main groups including: i) Cost-Related, ii) Implementation Time, iii) Vendor-Related, iv) User-Related, v) Technology-Related, vi) System-Related, and vii)Organizational Requirements. Original Paper: Hegazy, A. E. F. A., ElBattah, M...

Projects

Projects (4)
Project
Exploring ML-based methods for generating synthetic eye-tracking data.
Project
-Developing a methodology for transforming the dynamics of eye motion into a visual representation using the eye-tracking technology. -Applying Machine Learning to discover the eye-tracking visual patterns of ASD. -Developing predictive models that can support the early diagnosis of ASD.
Archived project
1) Gaining data-driven insights from the Irish Hip Fracture Database (IHFD) using unsupervised ML (e.g.clustering, rule mining). 2) Developing supervised ML models that can be used to predict care outcomes (e.g. length of stay) for elderly patients who undergo the hip fracture care in Ireland.