Correcting heterogeneous diagnostic bias when developing clinical prediction models using causal hidden Markov models
Fuente:
arXiv
Guardado en:
| Autores principales: | Benitez-Aurioles, Jose, Silva, Ricardo, McMillan, Brian, Sperrin, Matthew |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
The continuous net benefit: Assessing the clinical utility of prediction models when informing a continuum of decisions
por: Benitez-Aurioles, Jose, et al.
Publicado: (2024)
por: Benitez-Aurioles, Jose, et al.
Publicado: (2024)
Understanding algorithmic fairness for clinical prediction in terms of subgroup net benefit and health equity
por: Benitez-Aurioles, Jose, et al.
Publicado: (2024)
por: Benitez-Aurioles, Jose, et al.
Publicado: (2024)
Flexible unimodal density estimation in hidden Markov models
por: Koslik, Jan-Ole, et al.
Publicado: (2025)
por: Koslik, Jan-Ole, et al.
Publicado: (2025)
Scale dependence in hidden Markov models for animal movement
por: Michelot, Théo, et al.
Publicado: (2025)
por: Michelot, Théo, et al.
Publicado: (2025)
Detecting disease progression from animal movement using hidden Markov models
por: Kim, Dongmin, et al.
Publicado: (2025)
por: Kim, Dongmin, et al.
Publicado: (2025)
Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies
por: Sidrow, Evan, et al.
Publicado: (2024)
por: Sidrow, Evan, et al.
Publicado: (2024)
Can the hot hand phenomenon be modelled? A Bayesian hidden Markov approach
por: Calvo, Gabriel, et al.
Publicado: (2023)
por: Calvo, Gabriel, et al.
Publicado: (2023)
Expectile hidden Markov regression models for analyzing cryptocurrency returns
por: Foroni, Beatrice, et al.
Publicado: (2023)
por: Foroni, Beatrice, et al.
Publicado: (2023)
Stability of clinical prediction models developed using statistical or machine learning methods
por: Riley, Richard D, et al.
Publicado: (2022)
por: Riley, Richard D, et al.
Publicado: (2022)
Inference on the state process of periodically inhomogeneous hidden Markov models for animal behavior
por: Koslik, Jan-Ole, et al.
Publicado: (2023)
por: Koslik, Jan-Ole, et al.
Publicado: (2023)
Modelling multi-scale state-switching functional data with hidden Markov models
por: Sidrow, Evan, et al.
Publicado: (2021)
por: Sidrow, Evan, et al.
Publicado: (2021)
Bayesian inference for hidden Markov models under genuine multimodality with application to ecological time series
por: Gallegos-Herrada, Marco A., et al.
Publicado: (2026)
por: Gallegos-Herrada, Marco A., et al.
Publicado: (2026)
Estimating parameters of continuous-time multi-chain hidden Markov models for infectious diseases
por: Bouzalmat, Ibrahim, et al.
Publicado: (2024)
por: Bouzalmat, Ibrahim, et al.
Publicado: (2024)
A capture-recapture hidden Markov model framework for register-based inference of population size and dynamics
por: Brown, Lucy Y, et al.
Publicado: (2026)
por: Brown, Lucy Y, et al.
Publicado: (2026)
Bayesian Nonhomogeneous hidden Markov models to leverage routine in physical activity monitoring with informative wear time
por: Cantoni, Beatrice, et al.
Publicado: (2025)
por: Cantoni, Beatrice, et al.
Publicado: (2025)
Improved order selection method for hidden Markov models: a case study with movement data
por: Dupont, Fanny, et al.
Publicado: (2024)
por: Dupont, Fanny, et al.
Publicado: (2024)
Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market
por: Foroni, Beatrice, et al.
Publicado: (2023)
por: Foroni, Beatrice, et al.
Publicado: (2023)
Estimating the distance at which narwhal $(\textit{Monodon monoceros})$ respond to disturbance: a penalized threshold hidden Markov model
por: Dupont, Fanny, et al.
Publicado: (2026)
por: Dupont, Fanny, et al.
Publicado: (2026)
Quantifying sleep apnea heterogeneity using hierarchical Bayesian modeling
por: Palmer, Glenn, et al.
Publicado: (2025)
por: Palmer, Glenn, et al.
Publicado: (2025)
Detecting clinician implicit biases in diagnoses using proximal causal inference
por: Liu, Kara, et al.
Publicado: (2025)
por: Liu, Kara, et al.
Publicado: (2025)
Finite-sample bias-variance tradeoff with variables related to trial participation inserted into causal forest models for ensuring generalizability
por: Hamaya, Rikuta, et al.
Publicado: (2025)
por: Hamaya, Rikuta, et al.
Publicado: (2025)
Bayesian hidden Markov models for latent variable labeling assignments in conflict research: application to the role ceasefires play in conflict dynamics
por: Williams, Jonathan P, et al.
Publicado: (2021)
por: Williams, Jonathan P, et al.
Publicado: (2021)
Extending finite mixture models with skew-normal distributions and hidden Markov models for time series
por: Nigri, Andrea, et al.
Publicado: (2025)
por: Nigri, Andrea, et al.
Publicado: (2025)
How to develop, externally validate, and update multinomial prediction models
por: Gehringer, Celina K, et al.
Publicado: (2023)
por: Gehringer, Celina K, et al.
Publicado: (2023)
A likelihood-based sensitivity analysis for addressing publication bias in meta-analysis of diagnostic studies using exact likelihood
por: Hu, Taojun, et al.
Publicado: (2024)
por: Hu, Taojun, et al.
Publicado: (2024)
Combining missing data imputation and internal validation in clinical risk prediction models
por: Mi, Junhui, et al.
Publicado: (2024)
por: Mi, Junhui, et al.
Publicado: (2024)
Bayesian nonparametric mixtures of categorical directed graphs for heterogeneous causal inference
por: Castelletti, Federico, et al.
Publicado: (2024)
por: Castelletti, Federico, et al.
Publicado: (2024)
Dose optimization design accounting for unknown patient heterogeneity in cancer clinical trials
por: Silva, Rebecca B., et al.
Publicado: (2025)
por: Silva, Rebecca B., et al.
Publicado: (2025)
Understanding the European energy crisis through structural causal models
por: Tausendfreund, Anton, et al.
Publicado: (2025)
por: Tausendfreund, Anton, et al.
Publicado: (2025)
Handling missing data when estimating causal effects with Targeted Maximum Likelihood Estimation
por: Dashti, S. Ghazaleh, et al.
Publicado: (2021)
por: Dashti, S. Ghazaleh, et al.
Publicado: (2021)
Autoregressive models for panel data causal inference with application to state-level opioid policies
por: Antonelli, Joseph, et al.
Publicado: (2024)
por: Antonelli, Joseph, et al.
Publicado: (2024)
Limits of epidemic prediction using SIR models
por: Melikechi, Omar, et al.
Publicado: (2021)
por: Melikechi, Omar, et al.
Publicado: (2021)
Combining chains of Bayesian models with Markov melding
por: Manderson, Andrew A., et al.
Publicado: (2021)
por: Manderson, Andrew A., et al.
Publicado: (2021)
Detecting algorithmic bias in medical-AI models using trees
por: Smith, Jeffrey, et al.
Publicado: (2023)
por: Smith, Jeffrey, et al.
Publicado: (2023)
Seasonal bias-correction of daily precipitation over France using a stitch model designed for robust extremes representation
por: Philippe, Ear, et al.
Publicado: (2025)
por: Philippe, Ear, et al.
Publicado: (2025)
Logistic regression is not enough: The need for Bayesian nonparametric modelling for causal inference using observational data, exemplified by the 'gateway' effect
por: Foxon, Floe, et al.
Publicado: (2026)
por: Foxon, Floe, et al.
Publicado: (2026)
Nodal heterogeneity can induce ghost triadic effects in relational event models
por: Juozaitienė, Rūta, et al.
Publicado: (2022)
por: Juozaitienė, Rūta, et al.
Publicado: (2022)
Topic-informed dynamic mixture model for occupational heterogeneity in health risk behaviors
por: Schiavon, Lorenzo, et al.
Publicado: (2025)
por: Schiavon, Lorenzo, et al.
Publicado: (2025)
Comparing methods to assess treatment effect heterogeneity in general parametric regression models
por: Chen, Yao, et al.
Publicado: (2025)
por: Chen, Yao, et al.
Publicado: (2025)
A multilevel model with heterogeneous variances for snap timing in the National Football League
por: Nguyen, Quang, et al.
Publicado: (2025)
por: Nguyen, Quang, et al.
Publicado: (2025)
Ejemplares similares
-
The continuous net benefit: Assessing the clinical utility of prediction models when informing a continuum of decisions
por: Benitez-Aurioles, Jose, et al.
Publicado: (2024) -
Understanding algorithmic fairness for clinical prediction in terms of subgroup net benefit and health equity
por: Benitez-Aurioles, Jose, et al.
Publicado: (2024) -
Flexible unimodal density estimation in hidden Markov models
por: Koslik, Jan-Ole, et al.
Publicado: (2025) -
Scale dependence in hidden Markov models for animal movement
por: Michelot, Théo, et al.
Publicado: (2025) -
Detecting disease progression from animal movement using hidden Markov models
por: Kim, Dongmin, et al.
Publicado: (2025)