Results 11 to 20 of about 28,926,907 (345)
Deep Recurrent Survival Analysis [PDF]
AAAI Conference on Artificial Intelligence, 2018 Survival analysis is a hotspot in statistical research for modeling time-to-event information with data censorship handling, which has been widely used in many applications such as clinical research, information system and other fields with survivorship ...
Qin, Jiarui +6 more
core +2 more sources
Deep learning for survival analysis: a review [PDF]
Artificial Intelligence Review, 2023 The influx of deep learning (DL) techniques into the field of survival analysis in recent years has led to substantial methodological progress; for instance, learning from unstructured or high-dimensional data such as images, text or omics data.
Simon Wiegrebe +3 more
semanticscholar +1 more source
Conformalized Survival Analysis. [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2021 Existing survival analysis techniques heavily rely on strong modelling assumptions and are, therefore, prone to model misspecification errors. In this paper, we develop an inferential method based on ideas from conformal prediction, which can wrap around
E. Candès, Lihua Lei, Zhimei Ren
semanticscholar +1 more source
SurvTRACE: transformers for survival analysis with competing events [PDF]
ACM International Conference on Bioinformatics, Computational Biology and Biomedicine, 2021 In medicine, survival analysis studies the time duration to events of interest such as mortality. One major challenge is how to deal with multiple competing events (e.g., multiple disease diagnoses).
Zifeng Wang, Jimeng Sun
semanticscholar +1 more source
Journal of Medical Internet Research, 2021 Background Survival analysis is a cornerstone of medical research, enabling the assessment of clinical outcomes for disease progression and treatment efficiency.
A. Lánczky, Balázs Győrffy
semanticscholar +1 more source
Bias by censoring for competing events in survival analysis
British medical journal, 2022 In survival analysis, competing events preclude the occurrence of the event of interest. The censoring of competing events is common in medical studies but leads to biased cumulative incidence estimators.
M. Coemans +4 more
semanticscholar +1 more source
Pancancer survival analysis of cancer hallmark genes
Scientific Reports, 2020 Cancer hallmark genes are responsible for the most essential phenotypic characteristics of malignant transformation and progression. In this study, our aim was to estimate the prognostic effect of the established cancer hallmark genes in multiple ...
Á. Nagy, G. Munkácsy, Balázs Győrffy
semanticscholar +1 more source
Pharmaceutics, 2023 (1) Background: Oxidative stress is crucial in carcinogenesis and the response of tumors to treatment. Antioxidant genes are important determinants of resistance to chemotherapy and radiotherapy.
Nadire Özenver, Thomas Efferth
doaj +1 more source
Applied Sciences, 2023 One of the most prominent issues the ever-growing open-source software community faces is the abundance of buggy code. Well-established version control systems and repository hosting services such as GitHub and Maven provide a checks-and-balances ...
Elia Eiroa-Lledo +4 more
doaj +1 more source
Glioma Survival Analysis Empowered With Data Engineering—A Survey
IEEE Access, 2021 Survival analysis is a critical task in glioma patient management due to the inter and intra tumor heterogeneity. In clinical practice, clinicians estimate the survival with their experience, which can be biased and optimistic.
Navodini Wijethilake +5 more
semanticscholar +1 more source