Results 211 to 220 of about 336,506 (292)

A Hybrid Semi‐Inverse Variational and Machine Learning Approach for the Schrödinger Equation

Advanced Physics Research, EarlyView.
A hybrid semi‐inverse variational and machine‐learning framework is presented for solving the Schrödinger equation with complex quantum potentials. Physics‐based variational solutions generate high‐quality training data, enabling Random Forest and Neural Network models to deliver near‐perfect energy predictions.
Khalid Reggab, Houssam Eddine Hailouf, Kingsley Onyebuchi Obodo, Mireille Megnidio‐Tchoukouegno, Mohammed Benali Kanoun, Souraya Goumri‐Said   +5 more
wiley   +1 more source

Using multimodal PET+MR data as conditional generative adversarial network inputs improves pseudo-CT and attenuation correction estimates for brain PET/MR. [PDF]

Am J Nucl Med Mol Imaging
Fisher J, Anaya E, Chinn G, Levin CS.
europepmc   +1 more source

Modeling and parameter estimation for fractional large‐scale interconnected Hammerstein systems

Asian Journal of Control, EarlyView.
Abstract This paper addresses the challenge of modeling and identifying large‐scale interconnected systems exhibiting memory effects, hereditary properties, and non‐local interactions. We propose a fractional‐order extension of the Hammerstein architecture that incorporates Grünwald–Letnikov operators to capture complex dynamics through multiple ...
Mourad Elloumi, Omar Naifar, Imed Bouzida   +2 more
wiley   +1 more source

Analysis of Short-Term Subjective Well-Being/Comfort and Its Correlation to Different EEG Metrics. [PDF]

Sensors (Basel)
Wutzl B, Leibnitz K, Ohsita Y, Murata M.
europepmc   +1 more source

Mechanism‐informed machine learning for individualized tacrolimus dose adjustment in the early post‐kidney transplant period

British Journal of Clinical Pharmacology, EarlyView.
Abstract Aim Tacrolimus dosing in the early post‐kidney transplant period is challenging due to a narrow therapeutic index and substantial interindividual pharmacokinetic (PK) variability. This study aimed to develop and validate mechanism‐informed machine learning (ML) models to support individualized tacrolimus dosing during this critical period ...
Hui Yu, Zihan Qin, Logan S. Smith, Jeong M. Park, Hao‐Jie Zhu   +4 more
wiley   +1 more source

Robust Trajectory Prediction for Mobile Robots via Minimum Error Entropy Criterion and Adaptive LSTM Networks. [PDF]

Entropy (Basel)
Xie D, Li Z, Zhang C, Wang C, Wei X.
europepmc   +1 more source

Metabolomic investigation of cisplatin‐induced acute kidney injury in paediatric cancer patients

British Journal of Clinical Pharmacology, EarlyView.
Aim Cisplatin causes acute kidney injury (AKI) in approximately 46% of paediatric cancer patients who receive it. Serum creatinine (SCr) is a poor biomarker of cisplatin nephrotoxicity, because there is a delay between cisplatin infusion and SCr elevation.
Yong Jin Lim, Amy Thachil, Kelly McMahon, Ross T. Tsuyuki, S. Rod Rassekh, Lesley G. Mitchell, Prasad Devarajan, Cherry Mammen, Bruce C. Carleton, Geoffrey D. E. Cuvelier, Victor A. Lewis, Colin J. D. Ross, Alexandra P. Zorzi, Sylvain Baruchel, Raveena Ramphal, Eric Bouffet, Mathieu Lemaire, Tom D. Blydt‐Hansen, Brad L. Urquhart, The Applying Biomarkers to Minimize Long‐Term Effects of Childhood/Adolescent Cancer Treatment (ABLE) Research Study Group, Tom Blydt‐Hansen, Bruce C. Carleton, Geoff D. E. Cuvelier, Sunil Desai, Prasad Devarajan, Conrad Fernandez, Adam Fleming, Paul Gibson, Caroline Laverdiere, Victor Lewis, Mary L. McBride, Bruno Michon, Shahrad Rod Rassekh, Colin J. D. Ross, Christine Sabapathy, Kirk R. Schultz, Michael Zappitelli, Alexandra Zorzi   +37 more
wiley   +1 more source

Dynamic transfer learning with co-occurrence-guided multi-source fusion for urban spatio-temporal crime prediction. [PDF]

Front Big Data
Cui C, Zheng Z, Du H, Wang W.
europepmc   +1 more source