Results 231 to 240 of about 30,189 (295)

A hybrid AI-genetic algorithm framework for the optimization of polymer flooding strategies: a numerical simulation-based approach. [PDF]

Sci Rep
Nourizadeh M, Khosravi R, Simjoo M, Chahardowli M.   +3 more
europepmc   +1 more source

STELLAR‐CB: Synthetic Temporal LSTM for Livestock Activity Recognition—Cow Behaviour

Veterinary Medicine and Science, Volume 12, Issue 4, July 2026.
This study introduces a novel framework combining LSTM networks with SMOTE to address class imbalance in precision livestock farming. It improves the detection of rare behaviours in livestock, achieving state‐of‐the‐art performance while reducing computational overhead, offering a practical, breed‐agnostic solution for enhancing automated behaviour ...
Ghufran Ahmed, Rauf Ahmed Shams Malick, Ahmad Sami Al‐Shamayleh, Muhammad Adnan Ayub, Usama Antuley, Twaha Ahmed Minai, Muhammad Faisal Khan, Muhammad Faraz Hyder, Muhammad Mubashir Khan, Adnan Akhunzada   +9 more
wiley   +1 more source

Developing and internally validating AI-based aging resilience biomarkers in non-human primates. [PDF]

J Gerontol A Biol Sci Med Sci
Bennett RF, Speiser JL, Olson JD, Schaaf GW, Register TC, Cox LA, Cline JM, Quillen EE.   +7 more
europepmc   +1 more source

Unified Attention Recurrent Neural Network for Bias Correction of MJO Prediction

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 7, July 2026.
Abstract In global subseasonal forecasting using dynamical models, correcting the systematic biases of Madden–Julian Oscillation (MJO) predictions has proven critical, particularly due to issues of rapid amplitude damping and phase distortion. To address these biases, recent studies have demonstrated that deep learning offers a promising solution by ...
Yiyi Guo, Vassili Kitsios, Tingru Cui, Liuhua Peng, Feng Liu   +4 more
wiley   +1 more source

Zero-shot prediction of drug responses using biologically informed neural networks trained on phosphoproteomic timeseries. [PDF]

PLoS Comput Biol
Antonopoulos K, Nordenstorm O, Nilsson A.   +2 more
europepmc   +1 more source

Newborns' Language Discrimination May Not Reflect Sensitivity to Speech Rhythm: Evidence From Computational Modeling

Developmental Science, Volume 29, Issue 4, July 2026.
ABSTRACT Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm—the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal ...
Ruolan Leslie Famularo, Ali Aboelata, Thomas Schatz, Naomi H. Feldman   +3 more
wiley   +1 more source

Comparing the Use of Measured and Smoothed Data in Forecasting Visual Field Tests Using Deep Learning. [PDF]

Ophthalmol Sci
Abbasi A, Gowrisankaran S, Lin WC, Song X, Antony BJ, Wollstein G, Schuman JS, Ishikawa H.   +7 more
europepmc   +1 more source

Machine Learning‐Based Loan Approval Automation: Enhancing Efficiency, Accuracy and Fairness in Credit Decision‐Making

Expert Systems, Volume 43, Issue 7, July 2026.
ABSTRACT Traditional loan approval processes are manual, time‐consuming and susceptible to human bias. This research develops a machine learning‐based system to automate loan eligibility assessment while enhancing efficiency, accuracy and fairness in credit decision‐making. We developed and compared multiple supervised ML models—including Random Forest,
Mani Ghahremani, Hellen Amimo Otieno, Mishanil Kazreen, Stavros Shiaeles   +3 more
wiley   +1 more source

The Use of DeepQSAR Models for the Discovery of Peptides With Enhanced Antimicrobial and Antibiofilm Potential. [PDF]

Mol Inform
You J, Mslati H, Haney EF, Akhoundsadegh N, Hancock REW, Cherkasov A.   +5 more
europepmc   +1 more source

Advancing Marine Bioacoustics With Deep Generative Models: A Hybrid Augmentation Strategy for Southern Resident Killer Whale Detection

Marine Mammal Science, Volume 42, Issue 3, July 2026.
ABSTRACT Automated detection and classification of marine mammal vocalizations is critical for conservation and management efforts but is hindered by limited annotated datasets and the acoustic complexity of real‐world marine environments. Data augmentation has proven to be an effective strategy to address this limitation by increasing dataset ...
Bruno Padovese, Fabio Frazao, Michael Dowd, Ruth Joy   +3 more
wiley   +1 more source