10 papers · ranked by Valyu relevance
Nazanin Zahra Keshvari, Sara Asl Motaleb Nejad Sarkhab, Tara Shahmoradi, Mohammad Pourashory + 3 more
Omics datasets are inherently complex and involve an unmanageable number of factors, which render manual/traditional analyses unfruitful. Through the application of data-training protocols, the large number of parameters could be managed. Moreover, ML methods are generally categorized as either: Supervised ML: the…
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…
Yu Zhang, Hui Wang, Liping Zhang
Neonatal hyperbilirubinemia is common in early neonatal life, and delayed recognition of high-risk infants may result in bilirubin-induced neurological injury. Prediction models based on routinely available maternal, perinatal, neonatal, and standardized laboratory variables may support early risk stratification as an…
Charles de Kergariou, Helmut Hauser, David Correa
Advances in novel materials science enable structures to function as intelligent machines by embedding memory and learning capabilities directly into materials. Our work introduces a physical adaptive material motor unit neural network, leveraging a new generation of controllable actuators composed of wood- and carbon…
Mathias Claeys, Neil Fam, Xiaojiao Xiao, Tejas Vyas + 10 more
Background Patient selection for transcatheter mitral valve edge-to-edge repair (MTEER) remains challenging, particularly in individuals with complex mitral valve anatomy. Conventional risk scores incorporate limited clinical variables and do not adequately account for detailed echocardiographic features, resulting in…
Henrique Reis Aguiar, Matthias H. Hennig
Predictive coding is a powerful normative framework for understanding cortical computation, but it is still an open question how biologically plausible networks with local plasticity support predictive inference and representation learning. In this work we show that a recurrent excitatory-inhibitory circuit with purely…
Amélie Barozet, Vincent Cabeli, Jean Ogier du Terrail, Alexey Rukhovich + 6 more
The development of climate-resilient crops would be greatly accelerated by models able to reason directly over plant genomic sequences and to pinpoint trait-associated regions or loci. Anticipating the impact of DNA base changes (variants) remains challenging, and understanding regulatory mechanisms is still an active…
Maria B. Walter Costa, Rose Brouns, Maria Schreiber, Aristeidis Litos + 5 more
Understanding the adaptations of microorganisms to their environment is key to predicting the stability and dynamics of microbial communities. To uncover molecular mechanisms of environmental response, we extracted genomic features from 13,554 prokaryotic isolates, and trained machine learning models to identify which…
Priyanka Bhutada, Nitin Goyal, Tatsam K. Lakhankiya, Sai D. Narahari + 8 more
Artificial Intelligence (AI) frameworks for automating scientific research have shown strong performance on benchmarks, but their utility for real-world industrial research remains insufficiently characterized. Extending the analysis presented in the first paper of this series, we evaluated the same five advanced AI…
Francesco Carli, Polina Rusina, Lun Ai, Leonie Küchenhoff + 7 more
Language models and agents are increasingly used in biomedicine, but current benchmarks reward correct answers even when the underlying reasoning is flawed. Here we introduce Karenina, an open-source framework that turns expert knowledge into multi-dimensional evaluations of questions, conversations and autonomous…