Results 41 to 50 of about 422,144 (319)
Artificial Neural Networks and Deep Learning for Genomic Prediction of Continuous Outcomes [PDF]
, 2022 AbstractThis chapter provides elements for implementing deep neural networks (deep learning) for continuous outcomes. We give details of the hyperparameters to be tuned in deep neural networks and provide a general guide for doing this task with more probability of success.
Osval Antonio Montesinos López +2 more
openaire +1 more source
Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley +1 more source
Collective intelligence for deep learning: A survey of recent developments
Collective Intelligence, 2022 In the past decade, we have witnessed the rise of deep learning to dominate the field of artificial intelligence. Advances in artificial neural networks alongside corresponding advances in hardware accelerators with large memory capacity, together with ...
David Ha, Yujin Tang
doaj +1 more source
Exploiting more robust and efficacious deep learning techniques for modeling wind power with speed
Energy Reports, 2022 Sound analyses of the nonlinear relationship between wind speed and power generation are crucial for the advancement of wind energy optimization. As an emerging artificial intelligence technology, deep learning has received growing attention from energy ...
Hao Chen, Reidar Staupe-Delgado
doaj +1 more source
Deep Learning in Robotics: A Review of Recent Research
, 2017 Advances in deep learning over the last decade have led to a flurry of research in the application of deep artificial neural networks to robotic systems, with at least thirty papers published on the subject between 2014 and the present.
Gashler, Michael S., Pierson, Harry A.
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu +10 more
wiley +1 more source
Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients
, 2018 While neuroevolution (evolving neural networks) has a successful track record across a variety of domains from reinforcement learning to artificial life, it is rarely applied to large, deep neural networks.
Chen, Jay +3 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +15 more
wiley +1 more source
A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications
InformationDeep learning (DL) has become a core component of modern artificial intelligence (AI), driving significant advancements across diverse fields by facilitating the analysis of complex systems, from protein folding in biology to molecular discovery in ...
Ibomoiye Domor Mienye, Theo G. Swart
doaj +1 more source
Deep Learning and Its Applications in Biomedicine
Genomics, Proteomics & Bioinformatics, 2018 Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences.
Chensi Cao +8 more
doaj +1 more source