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- Norling, Rikke, et al.
(författare)
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Radiological imaging of the neck for initial decision-making in oral squamous cell carcinomas-A questionnaire survey in the Nordic countries
- 2012
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Ingår i: Acta Oncologica. - : Informa Healthcare. - 0284-186X .- 1651-226X. ; 51:3, s. 355-361
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Tidskriftsartikel (refereegranskat)abstract
- Background. Fast and accurate work-up is crucial to ensure the best possible treatment and prognosis for patients with head and neck cancer. The presence or absence of neck lymph node metastases is important for the prognosis and the choice of treatment. Clinical lymph node (N)-staging is done by palpation and diagnostic imaging of the neck. We investigated the current practice of the initial radiological work-up of patients with oral squamous cell carcinomas (OSCC) in the Nordic countries. Methods. A questionnaire regarding the availability and use of guidelines and imaging modalities for radiological N-staging in OSCC was distributed to 21 Head and Neck centres in Denmark (n = 4), Finland (n = 5), Iceland (n = 1), Norway (n = 4) and Sweden (n = 7). We also asked for a description of the radiological criteria for determining the lymph nodes as clinical positive (cN+) or negative (cN0). Results. All 21 Head and Neck centres responded to the questionnaire. Denmark and Finland have national guidelines, while Norway and Sweden have local or regional guidelines. Seventeen of the 19 centres with available guidelines recommended computed tomography (CT) of the cN0 neck. The waiting time may influence the imaging modalities used. Lymph node size was the most commonly used criteria for radiological cN+, but the cut-off measures vary from 0.8 to 2.0 cm. Conclusion. Overall, CT is the most commonly recommended and used imaging modality for OSCC. Despite availability of national guidelines the type and number of radiological examinations vary between centres within a country, but the implementation of a fast-track programme may facilitate fast access to imaging. The absence of uniform criteria for determining the lymph nodes of the neck as cN+ complicates the comparison of the accuracy of the imaging modalities. Well-defined radiological strategies and criteria are needed to optimise the radiological work-up in OSCC.
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| 3. |
- Olsson, Jimmy, et al.
(författare)
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An efficient particle-based online EM algorithm for general state-space models
- 2015
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Ingår i: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 48:28, s. 963-968
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Tidskriftsartikel (refereegranskat)abstract
- Estimating the parameters of general state-space models is a topic of importance for many scientific and engineering disciplines. In this paper we present an online parameter estimation algorithm obtained by casting our recently proposed particle-based, rapid incremental smoother (PaRIS) into the framework of online expectation-maximization (EM) for state-space models proposed by Cappé (2011). Previous such particle-based implementations of online EM suffer typically from either the well-known degeneracy of the genealogical particle paths or a quadratic complexity in the number of particles. However, by using the computationally efficient and numerically stable PaRIS algorithm for estimating smoothed expectations of timeaveraged sufficient statistics of the model we obtain a fast algorithm with very limited memory requirements and a computational complexity that grows only linearly with the number of particles. The efficiency of the algorithm is illustrated in a simulation study.
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| 4. |
- Olsson, Jimmy, et al.
(författare)
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Efficient parameter inference in general hidden Markov models using the filter derivatives
- 2016
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Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781479999880 ; , s. 3984-3988
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Konferensbidrag (refereegranskat)abstract
- Estimating online the parameters of general state-space hidden Markov models is a topic of importance in many scientific and engineering disciplines. In this paper we present an online parameter estimation algorithm obtained by casting our recently proposed particle-based, rapid incremental smoother (Paris) into the framework of recursive maximum likelihood estimation for general hidden Markov models. Previous such particle implementations suffer from either quadratic complexity in the number of particles or from the well-known degeneracy of the genealogical particle paths. By using the computational efficient and numerically stable Paris algorithm for estimating the needed prediction filter derivatives we obtain a fast algorithm with a computational complexity that grows only linearly with the number of particles. The efficiency and stability of the proposed algorithm are illustrated in a simulation study.
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| 5. |
- Olsson, Jimmy, et al.
(författare)
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Efficient particle-based online smoothing in general hidden Markov models : The PaRIS algorithm
- 2017
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Ingår i: Bernoulli. - : INT STATISTICAL INST. - 1350-7265 .- 1573-9759. ; 23:3, s. 1951-1996
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel algorithm, the particle-based, rapid incremental smoother (PaRIS), for efficient online approximation of smoothed expectations of additive state functionals in general hidden Markov models. The algorithm, which has a linear computational complexity under weak assumptions and very limited memory requirements, is furnished with a number of convergence results, including a central limit theorem. An interesting feature of PaRIS, which samples on-the-fly from the retrospective dynamics induced by the particle filter, is that it requires two or more backward draws per particle in order to cope with degeneracy of the sampled trajectories and to stay numerically stable in the long run with an asymptotic variance that grows only linearly with time.
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| 9. |
- Olsson, Jimmy, et al.
(författare)
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Particle-based online estimation of tangent filters with application to parameter estimation in nonlinear state-space models
- 2020
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Ingår i: Annals of the Institute of Statistical Mathematics. - : SPRINGER HEIDELBERG. - 0020-3157 .- 1572-9052. ; 72:2, s. 545-576
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel algorithm for efficient online estimation of the filter derivatives in general hidden Markov models. The algorithm, which has a linear computational complexity and very limited memory requirements, is furnished with a number of convergence results, including a central limit theorem with an asymptotic variance that can be shown to be uniformly bounded in time. Using the proposed filter derivative estimator, we design a recursive maximum likelihood algorithm updating the parameters according the gradient of the one-step predictor log-likelihood. The efficiency of this online parameter estimation scheme is illustrated in a simulation study.
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| 10. |
- Westerborn, Johan, et al.
(författare)
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EFFICIENT PARTICLE-BASED ONLINE SMOOTHING IN GENERAL HIDDEN MARKOV MODELS
- 2014
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Ingår i: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. - 1520-6149.
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Tidskriftsartikel (refereegranskat)abstract
- This paper deals with the problem of estimating expectations of sums of additive functionals under the joint smoothing distribution in general hidden Markov models. Computing such expectations is a key ingredient in any kind of expectation-maximization-based parameter inference in models of this sort. The paper presents a computationally efficient algorithm for online estimation of these expectations in a forward manner. The proposed algorithm has a linear computational complexity in the number of particles and does not require old particles and weights to be stored during the computations. The algorithm avoids completely the well-known particle path degeneracy problem of the standard forward smoother. This makes it highly applicable within the framework of online expectation-maximization methods. The simulations show that the proposed algorithm provides the same precision as existing algorithms at a considerably lower computational cost.
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