Gilles Dequen

• PhD
• Professor (Full) at University of Picardie Jules Verne

Background: Overcrowded emergency departments (EDs) create significant challenges for patient management and hospital efficiency. In response, Amiens Picardy University Hospital (APUH) developed the “Prediction of the Patient Pathway in the Emergency Department” (3P-U) model to enhance patient flow management. Objectives: To develop and clinically...

Blockchain is a distributed ledger that various applications can use to store data in a secure, decentralized, and immutable manner. The key piece in a blockchain is the consensus algorithm that different blockchain nodes run to obtain mutual agreement. While the Practical Byzantine Fault Tolerant (PBFT) is one of the most used algorithms and provi...

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterised by challenges in social communication, repetitive behaviours, and restricted interests [1]. Early and accurate diagnosis is critical for effective intervention, enabling individuals with ASD to achieve better developmental outcomes and an improved quality of life...

Large Language Models (LLMs) hold promise for advancing Emergency Medicine by enhancing operational efficiency and supporting decision-making. This scoping review explores the ethical, legal, and global considerations influencing LLM deployment in emergency care. Key ethical concerns, including patient safety, data privacy, and transparency, emphas...

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 complex models, such as neural networks, by revealing the reasoning behind predictions. However, a n...

With the success of blockchains for providing a high security platform for distributed systems, new challenges are presented in relation with the deployment of this technology for IoT applications with time constraints. In this paper, we present a new lightweight blockchain platform that is scalable to hold a large number of transactions and with a...

The k-anonymity problem introduced by Samarati and Sweeney in 1998, guarantees that it is impossible to distinguish user data from at least (k − 1) others in the same database. The methods used to achieve k-anonymity result in an information loss as the data in the database is modified, making it less accurate through a process of generalization or...

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 model for predicting patient admissions to the emergency department based on triage notes. We utilize...

Recently, blockchain technology has emerged as a revolutionary innovation with its distributed ledger feature that allows applications to store and transmit data in a secure, transparent, and immutable manner. One of the main ideas of blockchain technology is the consensus mechanism for reaching an agreement on the state of the distributed ledger....

La recherche sur l’intelligence artificielle (IA) appliquée à la médecine d’urgence et son utilisation au quotidien dans les structures d’urgences (SU) ont augmenté significativement ces dernières années. L’IA doit être considérée comme un outil d’aide à la prise en charge diagnostique et thérapeutique des patients et d’amélioration de l’organisati...

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). This accepted information bias can be managed in various ways: dropping patients with missing data...

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. However, making an accurate diagnosis of autism remains a challenging task, which requires an inte...

The French Society of Pathology (SFP) organized its first data challenge in 2020 with the help of the Health Data Hub (HDH). The organization of this event first consisted of recruiting nearly 5000 cervical biopsy slides obtained from 20 pathology centers. After ensuring that patients did not refuse to include their slides in the project, the slide...

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 variety of hurdles such as privacy concerns, or lack of sharing incentives. In this regard, this study a...

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...

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 variety of hurdles such as privacy concerns, or lack of sharing incentives. In this regard, this study a...

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...

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...

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...

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...

9th IEEE International Conference on Healthcare Informatics (IEEE ICHI), ELECTR NETWORK, AUG 09-12, 2021

Over the last decade, there have been significant efforts in developing efficient XOR-enabled SAT solvers for cryptographic applications. In [22] we proposed a solver specialised to cryptographic problems, and more precisely to instances arising from the index calculus attack on the discrete logarithm problem for elliptic curve-based cryptosystems....

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....

Parallel versions of collision search algorithms require a significant amount of memory to store a proportion of the points computed by the pseudo-random walks. Implementations available in the literature use a hash table to store these points and allow fast memory access. We provide theoretical evidence that memory is an important factor in determ...

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...

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....

In a rapidly changing territory, energy networks must be increasingly responsive and flexible. New models of multi-fluid management and energy production are being created and developed on national and international level. This involves the use, monitoring and supervision of many sensors that reports lot of data. This paper deals with the secure ma...

New trends highlight the use of delegated authentication solutions where identity providers do not need to synchronize user credentials with services. It is a facility for service providers and also for users who do not have to create multiple accounts. Different solutions for single sign-on and delegated authentication exist. Most of these solutio...

k-anonymity is a commonly used anonymization principle. It provides an anonymous table by grouping the individuals of the table in sets of at least k elements. This principle guarantees a good privacy while limiting the data alteration. Within the k-anonymization process, only quasi-identifier attributes are considered. Sensitive attributes are not...

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...

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...

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...

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...

Cryptographic problems can often be reduced to solving Boolean polynomial systems, whose equivalent logical formulas can be treated using SAT solvers. Given the algebraic nature of the problem, the use of the logical XOR operator is common in SAT-based cryptanalysis. Recent works have focused on advanced techniques for handling parity (XOR) constra...

Logical cryptanalysis, first introduced by Massacci in 2000, is a viable alternative to common algebraic cryptanalysis techniques over boolean fields. With xor operations being at the core of many cryptographic problems, recent research in this area has focused on handling xor clauses efficiently. In this paper, we investigate solving the point dec...

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...

Models for cryptographic problems are often expressed as boolean polynomial systems, whose equivalent logical formulas can be treated using SAT solvers. Given the algebraic nature of the problem, the use of the logical XOR operator is common in SAT-based cryptanalysis. Recent works have focused on advanced techniques for handling parity (XOR) const...

Secure Data sharing has become an ubiquitous need. One way of pursuing it is to use Proxy Re-Encryption (PRE), which allows delegation of decryption rights selectively. This work tackles the problem of designing a Proxy Re-Encryption that is unidirectional and CCA-secure in the standard model without pairings. In (Zhang et al., 2013) they propose a...

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...

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...

In educational context (online or face-to-face), with increasing cohort size and the need for individualization, the question of partial or full automation of assessments is growing. This paper deals with preliminary works that tackle the question of automatic generation of assessment Tests that could guarantee fairness and reasonable difference, b...

In the context of Smart Grid Cities, legal obligations require that certain personal data must be stored in the long term and protected. To deal with confidentiality issues, we use the concept of Proxy Re-Encryption (PRE) which allows sharing encrypted data. We present the first implementation of the Chow’s algorithm, and propose an optimized insta...

Autism spectrum disorder (ASD) is a neurodevelopmental disorder quite wide and its numerous variations render diagnosis hard. Some works have proven that children suffering from autism have trouble keeping their attention and tend to have a less focused sight. On top of that, eye-tracking systems enable the recording of precise eye focus on a scree...

In this paper, the authors highlight the existence of close relations between the execution time, efficiency and number of communication rounds in a family of CGM-based parallel algorithms for the optimal binary search tree problem (OBST). In this case, these three parameters cannot be simultaneously improved. The family of CGM (Coarse Grained Mult...

This paper presents a methodology to derive CGM (Coarse Grain Multicomputer) parallel algorithms for the cost of the Optimal Binary Search Tree Problem (OBST Problem). Depending on the parameter we want to optimize, we derive an algorithm accordingly. Therefore a load balancing, an efficient and a minimum communication rounds algorithms are obtaine...

In recent years, studies about the SATisfiability Problem (short for SAT) were more and more numerous because of its conceptual simplicity and ability to express a large set of various problems. Within a practical framework, works highlighting SAT impli-cations in real world problems had grown significantly. In this way, a new field called logical...

The combinatorial optimization problems are difficult to set up within a parallel context: a search-space is built during the computation and is explored in an irregular way. Moreover, the size of the search-space grows exponen-tially according to the size of the problem. Since the current processor industry is multiplying the number of cores in th...

Ce travail pose les bases d'une approche originale d'évaluation quasi-automatique ayant pour fondement le principe du QCM sur support papier. Ce système propose notamment une individualisation de l'évaluation garantissant pour chaque apprenant un sujet qui lui est propre permettant, entre autre, une limitation drastique de la possibilité de fraude...

The SATisfiability Problem is a core problem in mathematical logic and computing theory. In the last years, progresses have led it to be a great and competitive approach to practically solve a wide range of industrial and academic problems. Thus, the current SAT solving capacity allows the propositional formalism to be an interesting alternative to...

The SATisfiability Problem is a core problem in mathematical logic and computing theory. The last decade progresses have led it to be a great and competitive approach to practically solve a wide range of industrial and academic problems. Thus, the current SAT solving capacity allows the propositional formalism to be an interesting alternative to ta...

In spite of its computational complexity, the satisfiability problem is a great and competitive approach to solve a wide range of problems. This leads to have a strong demand for high-performance sat-solving tools in industry. Over the years, many different approaches and optimizations have been developed to tackle the problem more efficiently whil...

Satisfiability Problem is a great and competitive practical approach to solve a wide range of industrial and academic problems. The size and difficulty of the SAT instances have grown significantly over years thanks to solvers always more competitive. Among the recent solvers, the main part of them are sequential. Even if all of them include a very...

The last decade progresses have led the Satisfiability Problem (sat) to be a great and competitive practical approach to solve a wide range of industrial and academic problems. Thanks to these progresses, the size and difficulty of the sat instances has grown significantly. Among the recent solvers, a few are parallel and most of them use the messa...

The boolean satisfiability problem sat is a well-known NP-Complete problem, which is widely studied because of its conceptual simplicity. Nowadays the number of existing parallel SAT solvers is quite small. Furthermore, they are generally designed for large clusters using the message passing paradigm. These solvers are coarse grained application si...

This paper describes a new compact omnidirectional stereovision sensor that combines a single orthographic camera and four paraboloidal mirrors. Its geometry has been designed with the help of a stochastic optimization approach in order to minimize the 3D reconstruction error. In comparison with state-of-the-art sensors described in the literature,...

Recent research has focused on using the power of look-ahead to speed up the resolution of the Max-SAT problem. Indeed, look-ahead techniques such as Unit Propagation (UP) allow to find conflicts and to quickly reach the upper bound in a Branch-and-Bound algorithm, reducing the search-space of the resolution. In previous works, the Max-SAT solvers...

This paper deals with a compact catadioptric omnidirectional stereovision system based on a single camera and multi-mirrors (at least two mirrors). Many configurations were empirically designed in previous works with the aim to obtain a good 3D reconstruction accuracy. In this paper, we propose to use optimization techniques for omnidirectional cat...

Proving that a propositional formula is contradictory or unsatisfiable is a fundamental task in automated reasoning. This task is coNP-complete. Efficient algorithms are therefore needed when formulae are hard to solve. Random \(k-\) sat formulae provide a test-bed for algorithms because experiments that have become widely popular show clearly that...

Boolean Constraint Propagation (BCP) is recognized as one of the most use- ful technique for efficient satisfiability checking. In this paper a new extension of the scope of boolean constraint propagation is proposed. It makes an original use of BCP to achieve further reduction of boolean formulas. Considering the impli- cation graph generated by t...

Résumé La propagation de contraintes booléennes (BCP) est la technique la plus utile et la plus utilisée dans les solveurs SAT. Dans cet article, nous proposons une autre utilisation de cette technique dans le but de réduire, en termes de nombre de clauses et de longueur des clauses, la formule initiale. En considé-rant le graphe d'implications gén...

In this paper we generalize a heuristic that we have introduced previously for solving efficiently random 3-SAT formulae. Our heuristic is based on the notion of backbone, searching variables belonging to local backbones of a formula. This heuristic was limited to 3-SAT formulae. In this paper we generalize this heuristic by introducing a sub-heuri...

Introduction In [2] we presented a new branch variable selection heuristic for solving random 3-SAT formulae within a DPL-type procedure. This heuristic relied on the notion of backbone of a SAT formula, a concept recently introduced in a statistical physics study [3]. We now present the generalization of this heuristic for solving random k-SAT for...

To denote a (3,1,2)-conjugate orthogonal idempotent latin square of order n, the usual acronym is (3,1,2)-COILS(n). Up to now, existence of a (3,1,2)-COILS(n) had been proved for every positive integer n except n = 2, 3, 4, 6, for which the problem was answered in the negative, and n = 10, for which it remained open. In this paper, we use a compute...

Of late, new insight into the study of random -SAT formulae has been gained from the introduction of a concept inspired by models of physics, the 'back- bone' of a SAT formula which corresponds to the variables having a fixed truth value in all assign- ments satisfying the maximum number of clauses. In the present paper, we show that this concept,...

The Boolean Constraint Propagation (BCP) is a well-known helpful technique implemented in most state-of-the-art efficient satisfiability solvers. We propose in this paper a new use of the BCP to deduce sub-clauses from the associated implication graph. Our aim is to reduce the length of clauses thanks to the subsumption rule. We show how such exten...

kcnfs is a dpll based solver. kcnfs integrates a branching variable heuristic devoted essentially to prove the unsatisfiability of random k-sat formulae and which has been inspired by re- cent statistical physics work. This heuristic was presented in (DD01) and generalized to solve k- sat formulae with a renormalization strategy in (DD03). The loca...