Results 241 to 250 of about 333,902 (325)

Transfer-learning on federated observational healthcare data for prediction models using Bayesian sparse logistic regression with informed priors. [PDF]

J Am Med Inform Assoc
Li KM, Reps JM, Nishimura A, Schuemie MJ, Suchard MA.   +4 more
europepmc   +1 more source

Determinants of Profit Variability among Micro and Small Enterprises (MSEs) in Zambia

, 2014
Yordanos Gebremeskel
openalex   +2 more sources

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Enhancing interpretability for Bayesian basket trial designs by effective sample size. [PDF]

BMC Med Res Methodol
Chen X, Zhang J, Yang W, Jiang L, Li B, Yan F.   +5 more
europepmc   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Predicting tourism growth in Saudi Arabia with machine learning models for vision 2030 perspective. [PDF]

Sci Rep
Alsulami AG, Alharbi A, Khan UA, Al-Hejri AM, Alshamrani SS, Almotiri J.   +5 more
europepmc   +1 more source

Correction: Image discrimination robustness of classical image quality metrics: an analysis on MAE, MSE, ERGAS, LMSE, SSIM, SAM, UIQI, PSNR, NIQE, PIQE, SNR, VIF, FSIM, GMSD, and NCC [PDF]

Pınar Çivicioğlu, Erkan Beşdok
openalex   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Multiscale study of memory type simple ratio estimators in two stage sampling under exponentially weighted moving averages. [PDF]

PLoS One
Minhas KS, Semary HE, Jabeen R, Zaka A.
europepmc   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source