81 research outputs found
AUTHOR CORRECTION - ERS International Congress 2019:highlights from Best Abstract awardees
Lorna E. Latimer, Marieke Duiverman, Mahmoud I. Abdel-Aziz, Gulser Caliskan, Sara M. Mensink-Bout, Alberto Mendoza-Valderrey, Aurelien Justet, Junichi Omura, Karthi Srikanthan, Jana De Brandt. Breathe 2019; 15: e143–e149. This article from the December 2019 issue of Breathe was published with an error in the name of one of the authors. The corrected author list is shown above. The article has been corrected and republished online.</p
Total and partial cancer prevalence in the adult French population in 2008.
BACKGROUND: To provide estimations of partial and total prevalence of 24 cancer sites in France in 2008. The estimations of partial prevalence were compared with the previous estimations for 2002. METHODS: Nationwide estimations of incidence and survival data from cancer registries were used for partial prevalence. Nationwide incidence and mortality data were used to estimate total prevalence. RESULTS: At the end of 2008, in France, nearly 3 million people still alive had received a diagnosis of cancer. Of all prevalent cases, 36% were diagnosed 0 to 5 years earlier and 43% diagnosed 6 to 10 years earlier. The cancer sites with the highest prevalence were the prostate, the breast, and the colon-rectum. The changes in partial prevalence over 5 years (2002 to 2008) were considerable (+244,000 cases) and deemed to be highly related to changes in incidence. CONCLUSION: The present estimations update the French prevalence data and highlight the burden of cancer in the population, especially in the elderly. The methods of this study had the advantage of using recent incidence and survival data, which is necessary to show sudden changes in incidence trends and changes in survival that impact prevalence
Parametrized cosmological mass maps dataset
Parametrized cosmological mass maps dataset
This dataset consists of the non-tomographic training and testing set without noise and intrinsic alignments.
It was introduced in the following paper
Fluri, Janis, et al. "Cosmological constraints with deep learning from KiDS-450 weak lensing maps." Physical Review D 100.6 (2019): 063514.
Furthermore, this dataset is released with the following paper:
Perraudin, Nathanaël, et al. "Emulation of cosmological mass maps with conditional generative adversarial networks." arXiv preprint arXiv:2004.08139 (2020).
Code related to this dataset can be found in https://renkulab.io/projects/nathanael.perraudin/darkmattergan
Description
The simulation grid consists of different cosmologies assuming a flat LambdaCDM universe.
Each of these 57 configurations was run with different values of Omega_m and sigma_8, resulting in the following parameter grid.| Omega_m, sigma_8
0.101, 1.304
0.102, 1.125
0.103, 0.947
0.120, 1.178
0.123, 1.006
0.127, 0.836
0.137, 1.230
0.142, 1.063
0.148, 0.900
0.154, 1.281
0.156, 0.741
0.161, 1.119
0.169, 0.961
0.171, 1.331
0.178, 0.807
0.179, 1.173
0.188, 1.019
0.189, 0.659
0.196, 1.225
0.199, 0.870
0.207, 1.075
0.212, 0.727
0.219, 0.930
0.225, 1.129
0.227, 0.591
0.233, 0.791
0.238, 0.988
0.250, 0.658
0.254, 0.852
0.257, 1.043
0.269, 0.534
0.271, 0.723
0.273, 0.910
0.291, 0.601
0.291, 0.783
0.292, 0.966
0.311, 0.842
0.312, 0.664
0.314, 0.487
0.330, 0.898
0.332, 0.724
0.335, 0.552
0.352, 0.782
0.356, 0.614
0.370, 0.838
0.376, 0.673
0.382, 0.510
0.395, 0.730
0.402, 0.570
0.413, 0.784
0.421, 0.628
0.431, 0.475
0.440, 0.683
0.450, 0.533
0.458, 0.737
0.469, 0.589
0.487, 0.643
Each zip file in the dataset corresponds to 1 of these combinations and contains 12 files containing 1000 images.
The source galaxy redshift distribution corresponding to these maps is the full, non-tomographic redshift distribution n(z) from Fluri et. al.
The projected matter distribution was pixelised into images of size 128px x 128px, which correspond to 5deg x 5deg of the sky.
Eventually, the resulting dataset consists of 57 sets of 12'000 sky convergence maps for a total of samples.
Citations
If you use this dataset, please cite:
@article{perraudin2020emulation,
title={Emulation of cosmological mass maps with conditional generative adversarial networks},
author={Perraudin, Nathana{\"e}l and Marcon, Sandro and Lucchi, Aurelien and Kacprzak, Tomasz},
journal={arXiv preprint arXiv:2004.08139},
year={2020}
}
and
@article{fluri2019cosmological,
title={Cosmological constraints with deep learning from KiDS-450 weak lensing maps},
author={Fluri, Janis and Kacprzak, Tomasz and Lucchi, Aurelien and Refregier, Alexandre and Amara, Adam and Hofmann, Thomas and Schneider, Aurel},
journal={Physical Review D},
volume={100},
number={6},
pages={063514},
year={2019},
publisher={APS}
Hazard regression model and cure rate model in colon cancer relative survival trends: are they telling the same story?
Hazard regression models and cure rate models can be advantageously used in cancer relative survival analysis. We explored the advantages and limits of these two models in colon cancer and focused on the prognostic impact of the year of diagnosis on survival according to the TNM stage at diagnosis. The analysis concerned 9,998 patients from three French registries. In the hazard regression model, the baseline excess death hazard and the time-dependent effects of covariates were modelled using regression splines. The cure rate model estimated the proportion of 'cured' patients and the excess death hazard in 'non-cured' patients. The effects of year of diagnosis on these parameters were estimated for each TNM cancer stage. With the hazard regression model, the excess death hazard decreased significantly with more recent years of diagnoses (hazard ratio, HR 0.97 in stage III and 0.98 in stage IV, P 0.5). The two models were complementary and concordant in estimating colon cancer survival and the effects of covariates. They provided two different points of view of the same phenomenon: recent years of diagnosis had a favourable effect on survival, but not on cure
Cosmological N-body simulations: a challenge for scalable generative models: Tensorflow checkpoints
<p><strong>Tensorflow checkpoints: Cosmological N-body simulations: a challenge for scalable generative models</strong></p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper <strong>Cosmological N-body simulations: a challenge for scalable generative models</strong> by Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<pre><code>@inproceedings{perraudin2019cosmological,
title = {Cosmological N-body simulations: a challenge for scalable generative models},
author = {Nathana\"el, Perraudin and Ankit, Srivastava and Kacprzak, Tomasz and Lucchi, Aurelien and Hofmann, Thomas and R{\'e}fr{\'e}gier, Alexandre},
year = {2019},
archivePrefix = {arXiv},
eprint = {1908.05519},
url = {https://arxiv.org/abs/1908.05519},
}
</code></pre>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper<br>
**Cosmological N-body simulations: a challenge for scalable generative models** by<br>
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
Incidence of HIV-related anal cancer remains increased despite long-term combined antiretroviral treatment: results from the french hospital database on HIV.
PURPOSE: To study recent trends in the incidence of anal cancer in HIV-infected patients receiving long-term combined antiretroviral treatment (cART) compared with the general population. PATIENTS AND METHODS: From the French Hospital Database on HIV, we identified 263 cases of invasive anal squamous cell carcinoma confirmed histologically between 1992 and 2008. We compared incidence rates of anal cancer across four calendar periods: 1992-1996 (pre-cART period), 1997-2000 (early cART period), and 2001-2004 and 2005-2008 (recent cART periods). Standardized incidence ratios (SIRs) were calculated by using general population incidence data from the French Network of Cancer Registries. RESULTS: In HIV-infected patients, the hazard ratio (HR) in the cART periods versus the pre-cART period was 2.5 (95% CI, 1.28 to 4.98). No difference was observed across the cART calendar periods (HR, 0.9; 95% CI, 0.6 to 1.3). In 2005-2008, HIV-infected patients compared with the general population had an excess risk of anal cancer, with SIRs of 109.8 (95% CI, 84.6 to 140.3), 49.2 (95% CI, 33.2 to 70.3), and 13.1 (95% CI, 6.8 to 22.8) for men who have sex with men (MSM), other men, and women, respectively. Among patients with CD4 cell counts above 500/μL for at least 2 years, SIRs were 67.5 (95% CI, 41.2 to 104.3) when the CD4 nadir was less than 200/μL for more than 2 years and 24.5 (95% CI, 17.1 to 34.1) when the CD4 nadir was more than 200/μL. CONCLUSION: Relative to that in the general population, the risk of anal cancer in HIV-infected patients is still extremely high, even in patients with high current CD4 cell counts. cART appears to have no preventive effect on anal cancer, particularly in MSM
Author Correction: QUAREP-LiMi: a community endeavor to advance quality assessment and reproducibility in light microscopy
Comparison of a piezoceramic transducer and an EMAT for the omnidirectional transduction of SH0
A hierarchical approach for splitting truck platoons near network discontinuities
Truck platooning has attracted substantial attention due to its pronounced benefits in saving energy and promising business model in freight transportation. However, one prominent challenge for the successful implementation of truck platooning is the safe and efficient interaction with surrounding traffic, especially at network discontinuities where mandatory lane changes may lead to the decoupling of truck platoons. This contribution puts forward an efficient method for splitting a platoon of vehicles near network merges. A model-based bi-level control strategy is proposed. A supervisory tactical strategy based on a first-order car-following model with bounded acceleration is designed to maximize the flow at merge discontinuities. The decisions taken at this level include optimal vehicle order after the merge, new equilibrium gaps of automated trucks at the merging point, and anticipation horizon that the platoon members start to track the new equilibrium gaps. The lower-level operational layer uses a third-order longitudinal dynamics model to compute the optimal truck accelerations so that new equilibrium gaps are created when merging vehicles start to change lane and the transient maneuvers are efficient, safe and comfortable. The tactical decisions are derived from an analytic car-following model and the operational accelerations are controlled via model predictive control with guaranteed stability. Simulation experiments are provided in order to test the feasibility and demonstrate the performance and robustness of the proposed strategy.Transport and Plannin
Direct modeling of the crude probability of cancer death and the number of life years lost due to cancer without the need of cause of death: a pseudo-observation approach in the relative survival setting.
In population-based cancer studies, net survival is a crucial measure for population comparison purposes. However, alternative measures, namely the crude probability of death (CPr) and the number of life years lost (LYL) due to death according to different causes, are useful as complementary measures for reflecting different dimensions in terms of prognosis, treatment choice, or development of a control strategy. When the cause of death (COD) information is available, both measures can be estimated in competing risks setting using either cause-specific or subdistribution hazard regression models or with the pseudo-observation approach through direct modeling. We extended the pseudo-observation approach in order to model the CPr and the LYL due to different causes when information on COD is unavailable or unreliable (i.e., in relative survival setting). In a simulation study, we assessed the performance of the proposed approach in estimating regression parameters and examined models with different link functions that can provide an easier interpretation of the parameters. We showed that the pseudo-observation approach performs well for both measures and we illustrated their use on cervical cancer data from the England population-based cancer registry. A tutorial showing how to implement the method in R software is also provided
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