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  1. Article ; Online: Efficiency and tolerance of second-line triple BRAF inhibitor/MEK inhibitor/anti-PD1 combined therapy in BRAF mutated melanoma patients with central nervous system metastases occurring during first-line combined targeted therapy: a real-life survey.

    Fabre, Marie / Lamoureux, Anouck / Meunier, Laurent / Samaran, Quentin / Lesage, Candice / Girard, Céline / Du Thanh, Aurélie / Moulis, Lionel / Dereure, Olivier

    Melanoma research

    2024  Volume 34, Issue 3, Page(s) 241–247

    Abstract: Although current systemic therapies significantly improved the outcome of advanced melanoma, the prognosis of patient with central nervous system (CNS) metastases remains poor especially when clinically symptomatic. We aimed to investigate the efficiency ...

    Abstract Although current systemic therapies significantly improved the outcome of advanced melanoma, the prognosis of patient with central nervous system (CNS) metastases remains poor especially when clinically symptomatic. We aimed to investigate the efficiency of CNS targets and tolerance of second-line combined anti-PD1/dual-targeted anti-BRAF/anti-MEK therapy implemented in patients with CNS progression after initially efficient first-line combined targeted therapy in patients with BRAF-mutated melanoma in a real-life setting. A monocentric retrospective analysis including all such patients treated from January 2017 to January 2022 was conducted in our tertiary referral center. The response of CNS lesions to second-line triple therapy was assessed through monthly clinical and at least quarterly morphological (according to RECIST criteria) evaluation. Tolerance data were also collected. Seventeen patients were included with a mean follow-up of 2.59 (±2.43) months. Only 1 patient displayed a significant clinical and morphological response. No statistically significant difference was observed between patients receiving or not additional local therapy (mainly radiotherapy) as to response achievement. Immunotherapy was permanently discontinued in 1 patient owing to grade 4 toxicity. Mean PFS and OS after CNS progression were 2.59 and 4.12 months, respectively. In this real-life survey, the subsequent addition of anti-PD1 to combined targeted therapy in melanoma patients with upfront CNS metastases did not result in significant response of CNS targets in most BRAF mutated melanoma patients with secondary CNS progression after initially successful first-line combined targeted therapy.
    MeSH term(s) Humans ; Melanoma/drug therapy ; Melanoma/genetics ; Melanoma/pathology ; Female ; Male ; Proto-Oncogene Proteins B-raf/genetics ; Middle Aged ; Aged ; Retrospective Studies ; Central Nervous System Neoplasms/secondary ; Central Nervous System Neoplasms/drug therapy ; Adult ; Skin Neoplasms/drug therapy ; Skin Neoplasms/genetics ; Skin Neoplasms/pathology ; Protein Kinase Inhibitors/therapeutic use ; Protein Kinase Inhibitors/pharmacology ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use ; Immune Checkpoint Inhibitors/therapeutic use ; Immune Checkpoint Inhibitors/pharmacology ; Mutation ; Programmed Cell Death 1 Receptor/antagonists & inhibitors ; Aged, 80 and over
    Chemical Substances Proto-Oncogene Proteins B-raf (EC 2.7.11.1) ; BRAF protein, human (EC 2.7.11.1) ; Protein Kinase Inhibitors ; Immune Checkpoint Inhibitors ; Programmed Cell Death 1 Receptor
    Language English
    Publishing date 2024-03-28
    Publishing country England
    Document type Journal Article
    ZDB-ID 1095779-0
    ISSN 1473-5636 ; 0960-8931
    ISSN (online) 1473-5636
    ISSN 0960-8931
    DOI 10.1097/CMR.0000000000000963
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Infrared-induced hives.

    Aljaber, Faisal / Du-Thanh, Aurélie / Raison-Peyron, Nadia / Meunier, Laurent / Dereure, Olivier / Bourrain, Jean Luc

    The journal of allergy and clinical immunology. In practice

    2023  Volume 11, Issue 8, Page(s) 2581–2582

    MeSH term(s) Humans ; Urticaria/etiology ; Infrared Rays/adverse effects
    Language English
    Publishing date 2023-04-07
    Publishing country United States
    Document type Case Reports ; Journal Article
    ZDB-ID 2843237-X
    ISSN 2213-2201 ; 2213-2198
    ISSN (online) 2213-2201
    ISSN 2213-2198
    DOI 10.1016/j.jaip.2023.03.045
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings

    Scetbon, Meyer / Meunier, Laurent / Romano, Yaniv

    2021  

    Abstract: We propose a new conditional dependence measure and a statistical test for conditional independence. The measure is based on the difference between analytic kernel embeddings of two well-suited distributions evaluated at a finite set of locations. We ... ...

    Abstract We propose a new conditional dependence measure and a statistical test for conditional independence. The measure is based on the difference between analytic kernel embeddings of two well-suited distributions evaluated at a finite set of locations. We obtain its asymptotic distribution under the null hypothesis of conditional independence and design a consistent statistical test from it. We conduct a series of experiments showing that our new test outperforms state-of-the-art methods both in terms of type-I and type-II errors even in the high dimensional setting.
    Keywords Statistics - Machine Learning ; Computer Science - Machine Learning
    Publishing date 2021-10-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Asymptotic convergence rates for averaging strategies

    Meunier, Laurent / Legheraba, Iskander / Chevaleyre, Yann / Teytaud, Olivier

    2021  

    Abstract: Parallel black box optimization consists in estimating the optimum of a function using $\lambda$ parallel evaluations of $f$. Averaging the $\mu$ best individuals among the $\lambda$ evaluations is known to provide better estimates of the optimum of a ... ...

    Abstract Parallel black box optimization consists in estimating the optimum of a function using $\lambda$ parallel evaluations of $f$. Averaging the $\mu$ best individuals among the $\lambda$ evaluations is known to provide better estimates of the optimum of a function than just picking up the best. In continuous domains, this averaging is typically just based on (possibly weighted) arithmetic means. Previous theoretical results were based on quadratic objective functions. In this paper, we extend the results to a wide class of functions, containing three times continuously differentiable functions with unique optimum. We prove formal rate of convergences and show they are indeed better than pure random search asymptotically in $\lambda$. We validate our theoretical findings with experiments on some standard black box functions.
    Keywords Mathematics - Optimization and Control ; Computer Science - Neural and Evolutionary Computing
    Publishing date 2021-08-10
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: Scalable Lipschitz Residual Networks with Convex Potential Flows

    Meunier, Laurent / Delattre, Blaise / Araujo, Alexandre / Allauzen, Alexandre

    2021  

    Abstract: The Lipschitz constant of neural networks has been established as a key property to enforce the robustness of neural networks to adversarial examples. However, recent attempts to build $1$-Lipschitz Neural Networks have all shown limitations and ... ...

    Abstract The Lipschitz constant of neural networks has been established as a key property to enforce the robustness of neural networks to adversarial examples. However, recent attempts to build $1$-Lipschitz Neural Networks have all shown limitations and robustness have to be traded for accuracy and scalability or vice versa. In this work, we first show that using convex potentials in a residual network gradient flow provides a built-in $1$-Lipschitz transformation. From this insight, we leverage the work on Input Convex Neural Networks to parametrize efficient layers with this property. A comprehensive set of experiments on CIFAR-10 demonstrates the scalability of our architecture and the benefit of our approach for $\ell_2$ provable defenses. Indeed, we train very deep and wide neural networks (up to $1000$ layers) and reach state-of-the-art results in terms of standard and certified accuracy, along with empirical robustness, in comparison with other $1$-Lipschitz architectures.
    Keywords Computer Science - Machine Learning
    Subject code 006
    Publishing date 2021-10-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: Towards Consistency in Adversarial Classification

    Meunier, Laurent / Ettedgui, Raphaël / Pinot, Rafael / Chevaleyre, Yann / Atif, Jamal

    2022  

    Abstract: In this paper, we study the problem of consistency in the context of adversarial examples. Specifically, we tackle the following question: can surrogate losses still be used as a proxy for minimizing the $0/1$ loss in the presence of an adversary that ... ...

    Abstract In this paper, we study the problem of consistency in the context of adversarial examples. Specifically, we tackle the following question: can surrogate losses still be used as a proxy for minimizing the $0/1$ loss in the presence of an adversary that alters the inputs at test-time? Different from the standard classification task, this question cannot be reduced to a point-wise minimization problem, and calibration needs not to be sufficient to ensure consistency. In this paper, we expose some pathological behaviors specific to the adversarial problem, and show that no convex surrogate loss can be consistent or calibrated in this context. It is therefore necessary to design another class of surrogate functions that can be used to solve the adversarial consistency issue. As a first step towards designing such a class, we identify sufficient and necessary conditions for a surrogate loss to be calibrated in both the adversarial and standard settings. Finally, we give some directions for building a class of losses that could be consistent in the adversarial framework.
    Keywords Computer Science - Machine Learning
    Subject code 006
    Publishing date 2022-05-20
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; Online: On the Role of Randomization in Adversarially Robust Classification

    Gnecco-Heredia, Lucas / Chevaleyre, Yann / Negrevergne, Benjamin / Meunier, Laurent / Pydi, Muni Sreenivas

    2023  

    Abstract: Deep neural networks are known to be vulnerable to small adversarial perturbations in test data. To defend against adversarial attacks, probabilistic classifiers have been proposed as an alternative to deterministic ones. However, literature has ... ...

    Abstract Deep neural networks are known to be vulnerable to small adversarial perturbations in test data. To defend against adversarial attacks, probabilistic classifiers have been proposed as an alternative to deterministic ones. However, literature has conflicting findings on the effectiveness of probabilistic classifiers in comparison to deterministic ones. In this paper, we clarify the role of randomization in building adversarially robust classifiers. Given a base hypothesis set of deterministic classifiers, we show the conditions under which a randomized ensemble outperforms the hypothesis set in adversarial risk, extending previous results. Additionally, we show that for any probabilistic binary classifier (including randomized ensembles), there exists a deterministic classifier that outperforms it. Finally, we give an explicit description of the deterministic hypothesis set that contains such a deterministic classifier for many types of commonly used probabilistic classifiers, i.e. randomized ensembles and parametric/input noise injection.

    Comment: 10 pages main paper (27 total), 2 figures in main paper. Neurips 2023
    Keywords Computer Science - Machine Learning
    Subject code 006
    Publishing date 2023-02-14
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Diagnostic Accuracy of Digital Staining ex vivo Confocal Microscopy for Diagnosing and Subtyping Basal Cell Carcinoma in Fresh Pretherapeutic Punch Biopsies: A Monocentric Prospective Study.

    Bergeret, Blanche / Masset, Farzaneh / Bekoy, Yona D / Roger, Pascal / Habib, François / Ovtchinnikoff, Bernadette / Meunier, Laurent / Stoebner, Pierre E

    Dermatology (Basel, Switzerland)

    2022  , Page(s) 1–7

    Abstract: Background: Ex vivo confocal microscopy using fusion mode and digital staining (EVCM) scans unfixed fresh tissue and produces rapidly digitally stained images of very similar quality to classical pathology. We investigated whether EVCM could represent ... ...

    Abstract Background: Ex vivo confocal microscopy using fusion mode and digital staining (EVCM) scans unfixed fresh tissue and produces rapidly digitally stained images of very similar quality to classical pathology. We investigated whether EVCM could represent an alternative to the standard histological examination of the pretherapeutic basal cell carcinoma (BCC) punch biopsies.
    Objectives: The objective of the study was to assess diagnostic accuracy of EVCM versus traditional histopathological examination for diagnosing and subtyping clinically suspicious lesions of BCC in 3-mm fresh and nonfixed punch biopsies.
    Methods: In this prospective monocentric observational study, patients with clinically suspected BCC were consecutively enrolled. Punch biopsies were imaged using EVCM and subsequently processed for standard histologic examination (gold standard). EVCM images were examined by a dermatopathologist blinded to clinical aspect of the lesion and histopathological results. Concordance between the EVCM and histology analysis was calculated with Cohen's kappa (κ) statistic.
    Results: Sixty-six patients were recruited, and 106 biopsies were analyzed. EVCM correctly diagnosed 70/73 BCCs and 31/33 non-BCC lesions, corresponding to a sensitivity of 96% and a specificity of 94% (positive predictive value = 97%, negative predictive value = 91%). The EVCM assessment led to over-staging and under-staging of BCC subtypes in 5% and 11% of cases, respectively. It led to over-staging and under-staging of BCC depths in 5% and 15%, respectively. The kappa coefficient for concordance was 0.78 (95% confidence interval [CI]: 0.69-0.88) when considering BCC subtypes and 0.81 (95% CI: 0.72-0.90) when considering BCC depths.
    Conclusions: These results render EVCM as a promising option for "real-time" pretreatment evaluation of clinically suspected BCC lesions. Further larger randomized studies are needed to assess the efficiency of EVCM versus standard care in patients with clinically suspected BCC.
    Language English
    Publishing date 2022-05-05
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1099692-8
    ISSN 1421-9832 ; 1018-8665
    ISSN (online) 1421-9832
    ISSN 1018-8665
    DOI 10.1159/000524349
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Book ; Online: Variance Reduction for Better Sampling in Continuous Domains

    Meunier, Laurent / Doerr, Carola / Rapin, Jeremy / Teytaud, Olivier

    2020  

    Abstract: Design of experiments, random search, initialization of population-based methods, or sampling inside an epoch of an evolutionary algorithm use a sample drawn according to some probability distribution for approximating the location of an optimum. Recent ... ...

    Abstract Design of experiments, random search, initialization of population-based methods, or sampling inside an epoch of an evolutionary algorithm use a sample drawn according to some probability distribution for approximating the location of an optimum. Recent papers have shown that the optimal search distribution, used for the sampling, might be more peaked around the center of the distribution than the prior distribution modelling our uncertainty about the location of the optimum. We confirm this statement, provide explicit values for this reshaping of the search distribution depending on the population size $\lambda$ and the dimension $d$, and validate our results experimentally.
    Keywords Computer Science - Neural and Evolutionary Computing ; Computer Science - Machine Learning ; Statistics - Machine Learning
    Publishing date 2020-04-24
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: Advocating for Multiple Defense Strategies against Adversarial Examples

    Araujo, Alexandre / Meunier, Laurent / Pinot, Rafael / Negrevergne, Benjamin

    2020  

    Abstract: It has been empirically observed that defense mechanisms designed to protect neural networks against $\ell_\infty$ adversarial examples offer poor performance against $\ell_2$ adversarial examples and vice versa. In this paper we conduct a geometrical ... ...

    Abstract It has been empirically observed that defense mechanisms designed to protect neural networks against $\ell_\infty$ adversarial examples offer poor performance against $\ell_2$ adversarial examples and vice versa. In this paper we conduct a geometrical analysis that validates this observation. Then, we provide a number of empirical insights to illustrate the effect of this phenomenon in practice. Then, we review some of the existing defense mechanism that attempts to defend against multiple attacks by mixing defense strategies. Thanks to our numerical experiments, we discuss the relevance of this method and state open questions for the adversarial examples community.

    Comment: Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD)
    Keywords Computer Science - Machine Learning
    Publishing date 2020-12-04
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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