Results 101 to 110 of about 75,980 (291)

Bivariate Length-Biased Exponential Distribution under Progressive Type-II Censoring: Incorporating Random Removal and Applications to Industrial and Computer Science Data

Axioms
In this paper, we address the analysis of bivariate lifetime data from a length-biased exponential distribution observed under Type II progressive censoring with random removals, where the number of units removed at each failure time follows a binomial ...
Aisha Fayomi, Ehab M. Almetwally, Maha E. Qura   +2 more
doaj   +1 more source

Considering time-interaction terms using parametric survival models for interval-censoring data

Epidemiology, Biostatistics and Public Health, 2017
Background: Many of the variables which are investigated in survival research are time-invariant, i.e. their values do not change over time. But their effects, may yet vary over time.
Erfan Ghasemi, Alireza Akbarzadeh Baghban, Ahmadreza Baghestani, Saeed Asgary   +3 more
doaj   +1 more source

Foundation Model‐Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi‐Institutional Retrospective Study

Advanced Science, EarlyView.
FLARE, a multimodal AI framework, combines pathology slides, radiology scans, and clinical reports to predict colorectal cancer outcomes, even when some tests are missing. Evaluated retrospectively in 1679 patients from four medical centers, it consistently achieved the best prognostic accuracy and clearly separated high‐ and low‐risk groups.
Linhao Qu, Chengsheng Zhang, Yingyong Hou, Feng Tang, Weiqi Sheng, Dan Huang, Zhijian Song   +6 more
wiley   +1 more source

Analysis of Block Adaptive Type-II Progressive Hybrid Censoring with Weibull Distribution

Mathematics
The estimation of unknown model parameters and reliability characteristics is considered under a block adaptive progressive hybrid censoring scheme, where data are observed from a Weibull model.
Kundan Singh, Yogesh Mani Tripathi, Liang Wang, Shuo-Jye Wu   +3 more
doaj   +1 more source

HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning

Advanced Science, EarlyView.
HiST, a multiscale deep learning framework, reconstructs spatially resolved gene expression profiles directly from histological images. It accurately identifies tumor regions, captures intratumoral heterogeneity, and predicts patient prognosis and immunotherapy response.
Wei Li, Dong Zhang, Eryu Peng, Shijun Shen, Hamid Alinejad‐Rokny, Yao Liu, Junke Zheng, Cizhong Jiang, Youqiong Ye   +8 more
wiley   +1 more source

Experimental Survival Curves for Interval-Censored Data

Applied Statistics, 1973
A method is given for calculating from interval‐censored data an estimate of the c.d.f. which is analogous to the estimate derivable from right‐censored data by the life‐table technique. A Fortran implementation has been constructed by the author.
openaire   +2 more sources

Effectiveness of Pre‐Transplant Dual GLP‐1 Receptor Agonist and SGLT2 Inhibitor Therapy on All‐Cause Mortality in Organ Transplantation Candidates with Obesity and Type 2 Diabetes: a Target‐Trial Emulation

Advanced Science, EarlyView.
This target trial emulation in solid organ transplant candidates with obesity and type 2 diabetes evaluates whether pre‐transplant dual therapy with GLP‐1 receptor agonists plus SGLT2 inhibitors is associated with post‐transplant mortality and kidney graft outcomes compared with monotherapy or usual care, using multinational electronic health records ...
Yu‐Nan Huang, Min‐Yu Tsou, Pin‐Hung Li, Jo‐Ching Chen, Yen‐Liang Liu, Gideon Meyerowitz‐Katz, Tsung‐Hsun Tsai, Pen‐Hua Su   +7 more
wiley   +1 more source

Cox models with time-varying covariates and partly-interval censoring-A maximum penalised likelihood approach. [PDF]

Stat Med, 2023
Webb A, Ma J.
europepmc   +1 more source

Dynamic Predictions with Time-Dependent Covariates in Survival Analysis using Joint Modeling and Landmarking [PDF]

, 2013
A key question in clinical practice is accurate prediction of patient prognosis. To this end, nowadays, physicians have at their disposal a variety of tests and biomarkers to aid them in optimizing medical care.
Andrinopoulou, Eleni-Rosalina, Lesaffre, Emmanuel, Molenberghs, Geert, Murawska, Magdalena, Rizopoulos, Dimitris, Takkenberg, Johanna J. M.   +5 more
core  

A Subset of Pro‐inflammatory CXCL10+ LILRB2+ Macrophages Derives From Recipient Monocytes and Drives Renal Allograft Rejection

Advanced Science, EarlyView.
This study uncovers a recipient‐derived monocyte‐to‐macrophage trajectory that drives inflammation during kidney transplant rejection. Using over 150 000 single‐cell profiles and more than 850 biopsies, the authors identify CXCL10+ macrophages as key predictors of graft loss.
Alexis Varin, Jovanne Palvair, Lennie Messager, Jamal Bamoulid, Jasper Callemeyn, Mélanie Chaintreuil, Ludivine Dal Zuffo, Didier Ducloux, Imane Farhat, Mathieu Legendre, Laurent Martin, Florian Renosi, Xavier Roussel, Thibaut Vaulet, Maarten Naesens, Claire Tinel, Baptiste Lamarthée   +16 more
wiley   +1 more source