Zobrazeno 1 - 10
of 5 933
pro vyhledávání: '"Loiselle, A."'
Deep neural networks (DNNs) have been used to create models for many complex analysis problems like image recognition and medical diagnosis. DNNs are a popular tool within machine learning due to their ability to model complex patterns and distributi
Externí odkaz:
http://arxiv.org/abs/2405.06859
Autor:
Sarah Meulebrouck, Judith Merrheim, Gurvan Queniat, Cyril Bourouh, Mehdi Derhourhi, Mathilde Boissel, Xiaoyan Yi, Alaa Badreddine, Raphaël Boutry, Audrey Leloire, Bénédicte Toussaint, Souhila Amanzougarene, Emmanuel Vaillant, Emmanuelle Durand, Hélène Loiselle, Marlène Huyvaert, Aurélie Dechaume, Victoria Scherrer, Piero Marchetti, Beverley Balkau, Guillaume Charpentier, Sylvia Franc, Michel Marre, Ronan Roussel, Raphaël Scharfmann, Miriam Cnop, Mickaël Canouil, Morgane Baron, Philippe Froguel, Amélie Bonnefond
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Functional genetics has identified drug targets for metabolic disorders. Opioid use impacts metabolic homeostasis, although mechanisms remain elusive. Here, we explore the OPRD1 gene (encoding delta opioid receptor, DOP) to understand its im
Externí odkaz:
https://doaj.org/article/78b374b3ff9b43728d9fb6ee8aab174e
Autor:
Schein J, Cloutier M, Gauthier-Loiselle M, Catillon M, Meng Y, Libchaber B, Jiang F, Childress A
Publikováno v:
Patient Preference and Adherence, Vol Volume 18, Pp 1651-1664 (2024)
Jeff Schein,1 Martin Cloutier,2 Marjolaine Gauthier-Loiselle,2 Maryaline Catillon,3 Yan Meng,4 Beatrice Libchaber,2 Fanny Jiang,2 Ann Childress5 1Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, USA; 2Analysis Group, Inc, Mo
Externí odkaz:
https://doaj.org/article/957fa21c2ef448be85fd369a9dae31c9
Autor:
Jeff Schein, Martin Cloutier, Marjolaine Gauthier-Loiselle, Rebecca Bungay, Kathleen Chen, Deborah Chan, Annie Guerin, Ann Childress
Publikováno v:
Child and Adolescent Psychiatry and Mental Health, Vol 18, Iss 1, Pp 1-10 (2024)
Abstract Background Attention-deficit/hyperactivity disorder (ADHD) has been shown to pose considerable clinical and economic burden; however, research quantifying the excess burden attributable to common psychiatric comorbidities of ADHD among pedia
Externí odkaz:
https://doaj.org/article/659c683194254f228ea5bb79f1ca950a
Evaluating Access to Prescription Medications in the Atopic Dermatitis Patient Population in the USA
Autor:
Allison R. Loiselle, Raj Chovatiya, Isabelle J. Thibau, Jessica K. Johnson, Michele Guadalupe, Wendy Smith Begolka
Publikováno v:
Dermatology and Therapy, Vol 14, Iss 7, Pp 1811-1821 (2024)
Abstract Introduction Despite advances in atopic dermatitis (AD) treatments, many patients face challenges obtaining medications. This study aimed to determine the frequency and causes of insurance coverage delays and denials for AD prescriptions and
Externí odkaz:
https://doaj.org/article/0184152bda4d406b89d2a6e7015e9e33
Publikováno v:
Journal of Multidisciplinary Healthcare, Vol Volume 17, Pp 2623-2633 (2024)
Samar Attieh,1 Kelley Kilpatrick,2 Denis Chênevert,3 Marie-Pascale Pomey,4– 6 Carmen G Loiselle7– 9 1Department of Experimental Medicine, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC, Canada; 2Susan E. French Chair i
Externí odkaz:
https://doaj.org/article/f758d17b848940b5b259a2d76184ff8c
Publikováno v:
IFAC-PapersOnLine, Volume 55, Issue 37, 2022, Pages 615-620
Reinforcement learning (RL)-based driver assistance systems seek to improve fuel consumption via continual improvement of powertrain control actions considering experiential data from the field. However, the need to explore diverse experiences in ord
Externí odkaz:
http://arxiv.org/abs/2301.00904
Publikováno v:
IFAC-PapersOnLine, Volume 55, Issue 24, 2022, Pages 149-154
Reinforcement learning (RL)-based adaptive cruise control systems (ACC) that learn and adapt to road, traffic and vehicle conditions are attractive for enhancing vehicle energy efficiency and traffic flow. However, the application of RL in safety cri
Externí odkaz:
http://arxiv.org/abs/2301.00884
Publikováno v:
IFAC Papers Online Vol 55 (2022)
Eco-driving strategies have been shown to provide significant reductions in fuel consumption. This paper outlines an active driver assistance approach that uses a residual policy learning (RPL) agent trained to provide residual actions to default pow
Externí odkaz:
http://arxiv.org/abs/2212.07611
Publikováno v:
2022 American Control Conference
With the growing need to reduce energy consumption and greenhouse gas emissions, Eco-driving strategies provide a significant opportunity for additional fuel savings on top of other technological solutions being pursued in the transportation sector.
Externí odkaz:
http://arxiv.org/abs/2212.07594