External validation of a hidden Markov model for gamma‐based classification of anatomical changes in lung cancer patients using EPID dosimetry

2020 ◽  
Vol 47 (10) ◽  
pp. 4675-4682
Author(s):  
Cecile J. A. Wolfs ◽  
Nicolas Varfalvy ◽  
Richard A. M. Canters ◽  
Sebastiaan M. J. J. G. Nijsten ◽  
Djoya Hattu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Cancer Patients ◽  
Hidden Markov ◽  
External Validation ◽  
Lung Cancer Patients ◽  
Anatomical Changes ◽  
Epid Dosimetry

PH-0651: Validating a hidden Markov model for lung anatomical change classification using EPID dosimetry

2020 ◽  
Vol 152 ◽  
pp. S361-S362
Author(s):  
C. Wolfs ◽  
N. Varfalvy ◽  
R. Canters ◽  
S. Nijsten ◽  
L. Archambault ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Anatomical Change ◽  
Epid Dosimetry

An unsupervised Hidden Markov Model-based system for the detection and classification of blue whale vocalizations off Chile

Bioacoustics ◽  
2019 ◽  
Vol 29 (2) ◽  
pp. 140-167 ◽  
Author(s):  
Susannah J. Buchan ◽  
Rodrigo Mahú ◽  
Jorge Wuth ◽  
Naysa Balcazar-Cabrera ◽  
Laura Gutierrez ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Blue Whale ◽  
Model Based

A New Multiparametric Classification in Lung Cancer Patients - S.M.I.G.

1983 ◽  
Vol 69 (5) ◽  
pp. 437-443 ◽  
Author(s):  
Claudio Modini ◽  
Mario Albertucci ◽  
Franco Cicconetti ◽  
Donatella Tirindelli Danesi ◽  
Renzo Cristiani ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Growth Rate ◽  
Mortality Rate ◽  
Cancer Patients ◽  
Cell Type ◽  
Tnm System ◽  
Lung Cancer Patients ◽  
The Difference

The classification of bronchogenic carcinoma as a function of the prognosis is still an open field. The evaluation of stage, by use of the TNM system, and histologic cell type is not sufficient to guarantee a correct prognosis. The growth rate of the neoplasm is another important parameter. We propose a classification that takes into account the stage (S), histologic cell type (M), immune status (I) and the growth rate of the primary tumor (G): S.M.I.G. We studied 90 lung cancer patients according to the S.M.I.G. classification and we observed that their prognoses were directly correlated with their S.M.I.G. scores (the higher the score, the higher the 10-month mortality rate). The mortality rates within the first 10 months of follow-up were respectively 0%, 0%, 36.36%, 68%, 90.9% for the 5 groups obtained by S.M.I.G. The difference is statistically significant (P < 0.0075) and there is a linear correlation between the mortality rate and the score assigned to each group (R = 0.943; P < 0.05). The S.M.I.G. classification can predict the prognosis more efficiently than the usual classification (TNM) and histological cell type.

scholarly journals PO-0782 External validation of NTCP models for pneumonitis in lung cancer patients receiving proton therapy

2019 ◽  
Vol 133 ◽  
pp. S404-S405
Author(s):  
A. Niezink ◽  
V. Jain ◽  
O. Chouvalova ◽  
R. Wijsman ◽  
C. Muijs ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Proton Therapy ◽  
External Validation ◽  
Lung Cancer Patients

External Validation of a Survival Score for Limited-Stage Small Cell Lung Cancer Patients Treated with Chemoradiotherapy

Lung ◽  
2020 ◽  
Vol 198 (1) ◽  
pp. 201-206
Author(s):  
Lukas Käsmann ◽  
Reem Abdo ◽  
Chukwuka Eze ◽  
Maurice Dantes ◽  
Julian Taugner ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Patients ◽  
Cell Lung Cancer ◽  
External Validation ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Patients ◽  
Limited Stage ◽  
Survival Score
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