Results 221 to 230 of about 17,602 (258)

Channel Estimation with Hierarchical Sparse Bayesian Learning for ODDM Systems [PDF]

J. Z. Han, Xuehan Wang, Jingbo Tan, Jintao Wang, Yu Ting ZHANG, Hai Lin, Jinhong Yuan   +6 more
openalex  

Contrasting Approaches in the Implementation of GRADE Methodology in Guidelines for Haemophilia and Von Willebrand Disease

Haemophilia, EarlyView.
ABSTRACT Introduction The 2024 ISTH clinical practice guideline (CPG) for treatment of congenital haemophilia, the NBDF‐McMaster Guideline on Care Models for Haemophilia Management, and ASH ISTH NBDF WFH guidelines on the diagnosis and management of VWD all utilised GRADE methodology.
Mark W. Skinner, Manuela Albisetti, Jesús Ardila, Jan Astermark, Jan Blatny, Manuel Carcao, Pratima Chowdary, Nathan T. Connell, Miguel Crato, Yesim Dargaud, Roseline d'Oiron, Amy L. Dunn, Miguel A. Escobar, Carmen Escuriola‐Ettingshausen, Emna Gouider, Annie Harroche, Cedric Hermans, Victor Jimenez‐Yuste, Radoslaw Kaczmarek, Gili Kenet, Liane Khoo, Robert Klamroth, Florian Langer, David Lillicrap, Johnny Mahlangu, Christoph Male, Tadashi Matsushita, Sandrine Meunier, Wolfgang Miesbach, Beatrice Nolan, Johannes Oldenburg, Brian O'Mahony, Margareth Ozelo, Glenn F. Pierce, Gloria Ramos, Michael Recht, Olivia Romero‐Lux, Dawn Rotellini, Rita C. Santoro, Tammuella C. Singleton, Alok Srivastava, Sophie Susen, Kate Talks, Huyen Tran, Leonard A. Valentino, Jerzy Windyga, Renchi Yang, Maria Elisa Mancuso, also on behalf of AICE, AHAD‐AP, AHCDC, ATHN, CLAHT, EHC, French CRH & MHEMO, HTCCNC, NBDF, PEDNET, UKHCDO, WFH   +59 more
wiley   +1 more source

Anti-noise variational sparse Bayesian estimation ghost imaging based on 3Level factor graph. [PDF]

Sci Rep
Xiang S, Bai Y, Zhou Q, Chen J, Zhai J, Yin J, Liu T, Liu X, Huang X, Fu X.   +9 more
europepmc   +1 more source

Exploring a Subpopulation of MASLD Associated With New Onset of CKD Using Supervised Clustering Techniques

Hepatology Research, EarlyView.
The supervised clustering of metabolic dysfunction‐associated steatotic liver disease (MASLD) using a SHapley Additive exPlanations (SHAP)‐converted matrix reveals distinct subpopulations that improved risk stratification for new onset of chronic kidney disease (CKD).
Itaru Hosaka, Marenao Tanaka, Tatsuya Sato, Yukinori Akiyama, Keitaro Nishizawa, Rie Matsumori, Hiroki Aida, Wataru Kawaharata, Kei Nakata, Koki Abe, Toru Suzuki, Hidemichi Kouzu, Naoya Yama, Nagisa Hanawa, Masato Furuhashi   +14 more
wiley   +1 more source

Multiple Measurement Vector-based Sparse Bayesian Learning Channel Estimation for Efficient D2D Discovery and Pairing

Iqra Javid, Сибарам Хара
openalex   +2 more sources

Alternative Approaches for Estimating Highest‐Density Regions

International Statistical Review, EarlyView.
Summary Among the variety of statistical intervals, highest‐density regions (HDRs) stand out for their ability to effectively summarise a distribution or sample, unveiling its distinctive and salient features. An HDR represents the minimum size set that satisfies a certain probability coverage, and current methods for their computation require ...
Nina Deliu, Brunero Liseo
wiley   +1 more source

Bayesian deep learning for probabilistic aquifer vulnerability and uncertainty prediction. [PDF]

Sci Rep
Mengistu TD, Kim MG, Chung IM, Chang SW.
europepmc   +1 more source

Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels

International Statistical Review, EarlyView.
Summary Bayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted.
Wei Jing, Michail Papathomas, Silvia Liverani   +2 more
wiley   +1 more source

Efficient Super-Resolution Bayesian Eletromagnetic Brain Imaging. [PDF]

IEEE Trans Biomed Eng
Cai C, Qi X, Yan J, Shang Y, Sekihara K, Wu W, Nagarajan SS.   +6 more
europepmc   +1 more source

Medical Knowledge Integration Into Reinforcement Learning Algorithms for Dynamic Treatment Regimes

International Statistical Review, EarlyView.
Summary The goal of precision medicine is to provide individualised treatment at each stage of chronic diseases, a concept formalised by dynamic treatment regimes (DTR). These regimes adapt treatment strategies based on decision rules learned from clinical data to enhance therapeutic effectiveness.
Sophia Yazzourh, Nicolas Savy, Philippe Saint‐Pierre, Michael R. Kosorok   +3 more
wiley   +1 more source