Results 241 to 250 of about 1,820,384 (367)

Refining the Liver Donor Risk Index With Machine Perfusion: A Bayesian Approach. [PDF]

Clin Transl Gastroenterol
Tanaka T, Sewell D.
europepmc   +1 more source

An optimal Bayesian process control for flexible manufacturing processes

, 1992
Albert Ke-Jeng Hu
openalex   +1 more source

Association Between Liver Function Grade and Post‐Hepatectomy Liver Failure in Patients With Hepatocellular Carcinoma: A Latent Class Analysis

Annals of Gastroenterological Surgery, EarlyView.
We retrospectively analyzed clinical data from patients who underwent hepatectomy for hepatocellular carcinoma (HCC) using LCA‐based grading system. These findings provide a new risk stratification framework for the design of precision surgery to treat patients with HCC.
Ling Liu, Jintao Zheng, Ye Wang, Chenao Yang, Jiachen Zhang, Changku Jia   +5 more
wiley   +1 more source

Beyond the blank page: Frequentist and Bayesian perspectives on risk prediction algorithms. [PDF]

World J Gastrointest Oncol
Tustumi F, Maegawa FAB, Serrano Uson Junior PL.   +2 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

The evolution of public health statistical modeling approaches and how to advance their incorporation into modern arboviral surveillance. [PDF]

J Med Entomol
McCarter M, Self SCW, Ewing A, Kanyangarara M, Gunter SM, Nolan MS.   +5 more
europepmc   +1 more source

Real and nominal rigidities in price setting: A bayesian analysis using aggregate data

, 2009
Fang Yao
openalex   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source