Search

Your search keyword '"Pontieri, Luigi"' showing total 367 results
Start Over Author "Pontieri, Luigi"
367 results on '"Pontieri, Luigi"'

1. Discussion: Effective and Interpretable Outcome Prediction by Training Sparse Mixtures of Linear Experts

Author

Folino, Francesco, Pontieri, Luigi, and Sabatino, Pietro

Subjects
Computer Science - Machine Learning
Abstract

Process Outcome Prediction entails predicting a discrete property of an unfinished process instance from its partial trace. High-capacity outcome predictors discovered with ensemble and deep learning methods have been shown to achieve top accuracy performances, but they suffer from a lack of transparency. Aligning with recent efforts to learn inherently interpretable outcome predictors, we propose to train a sparse Mixture-of-Experts where both the ``gate'' and ``expert'' sub-nets are Logistic Regressors. This ensemble-like model is trained end-to-end while automatically selecting a subset of input features in each sub-net, as an alternative to the common approach of performing a global feature selection step prior to model training. Test results on benchmark logs confirmed the validity and efficacy of this approach., Comment: This paper summarizes results presented at workshop \emph{ML4PM 2023}, associated with conference ICPM 2023, October 23-27, 2023, Rome, Italy. 6 pages, 1 figure

Published
2024

3. Big Multiple Sclerosis Data network: an international registry research network

Author

Glaser, Anna, Butzkueven, Helmut, van der Walt, Anneke, Gray, Orla, Spelman, Tim, Zhu, Chao, Trojano, Maria, Iaffaldano, Pietro, Battaglia, Mario A., Lucisano, Giuseppe, Vukusic, Sandra, Vukusic, Irena, Casey, Romain, Horakova, Dana, Drahota, Jiri, Magyari, Melinda, Joensen, Hanna, Pontieri, Luigi, Elberling, Frederik, Klyve, Pernilla, Mouresan, Elena Flavia, Forsberg, Lars, and Hillert, Jan

Published
2024
Full Text
View/download PDF

12. Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery

Author

Folino, Francesco, Folino, Gianluigi, Guarascio, Massimo, Pontieri, Luigi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ceci, Michelangelo, editor, Flesca, Sergio, editor, Masciari, Elio, editor, Manco, Giuseppe, editor, and Raś, Zbigniew W., editor

Published
2022
Full Text
View/download PDF

14. Monomorium

Author

Pontieri, Luigi, Linksvayer, Timothy A., and Starr, Christopher K., editor

Published
2021
Full Text
View/download PDF

15. Prognostic Factors of Disease Activity in Newly Diagnosed Teriflunomide-treated Patients with Multiple Sclerosis—A Nationwide Danish Study (P6-6.016)

Author

Mahler, Mie Reith, primary, Magyari, Melinda, additional, Pontieri, Luigi, additional, Elberling, Frederik, additional, Weglewski, Arkadiusz, additional, Poulsen, Mai Bang, additional, Bekyarov, Plamen, additional, Illes, Zsolt, additional, Kant, Matthias, additional, Sejbaek, Tobias, additional, Stilund, Morten Leif Munding, additional, Rasmussen, Peter, additional, Brask, Maria, additional, Urbonaviciute, Inga, additional, and Sellebjerg, Finn, additional

Published
2024
Full Text
View/download PDF

16. Prognostic factors for disease activity in newly diagnosed teriflunomide-treated patients with multiple sclerosis: a nationwide Danish study

Author

Mahler, Mie Reith, primary, Magyari, Melinda, additional, Pontieri, Luigi, additional, Elberling, Frederik, additional, Holm, Rolf Pringler, additional, Weglewski, Arkadiusz, additional, Poulsen, Mai Bang, additional, Storr, Lars Kristian, additional, Bekyarov, Plamen Anzhelov, additional, Illes, Zsolt, additional, Kant, Matthias, additional, Sejbaek, Tobias, additional, Stilund, Morten Leif, additional, Rasmussen, Peter V, additional, Brask, Maria, additional, Urbonaviciute, Inga, additional, and Sellebjerg, Finn, additional

Published
2024
Full Text
View/download PDF

18. A Multi-view Ensemble of Deep Models for the Detection of Deviant Process Instances

Author

Folino, Francesco, Folino, Gianluigi, Guarascio, Massimo, Pontieri, Luigi, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Koprinska, Irena, editor, Kamp, Michael, editor, Appice, Annalisa, editor, Loglisci, Corrado, editor, Antonie, Luiza, editor, Zimmermann, Albrecht, editor, Guidotti, Riccardo, editor, Özgöbek, Özlem, editor, Ribeiro, Rita P., editor, Gavaldà, Ricard, editor, Gama, João, editor, Adilova, Linara, editor, Krishnamurthy, Yamuna, editor, Ferreira, Pedro M., editor, Malerba, Donato, editor, Medeiros, Ibéria, editor, Ceci, Michelangelo, editor, Manco, Giuseppe, editor, Masciari, Elio, editor, Ras, Zbigniew W., editor, Christen, Peter, editor, Ntoutsi, Eirini, editor, Schubert, Erich, editor, Zimek, Arthur, editor, Monreale, Anna, editor, Biecek, Przemyslaw, editor, Rinzivillo, Salvatore, editor, Kille, Benjamin, editor, Lommatzsch, Andreas, editor, and Gulla, Jon Atle, editor

Published
2020
Full Text
View/download PDF

19. Exploiting Temporal Convolution for Activity Prediction in Process Analytics

Author

Folino, Francesco, Guarascio, Massimo, Liguori, Angelica, Manco, Giuseppe, Pontieri, Luigi, Ritacco, Ettore, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Koprinska, Irena, editor, Kamp, Michael, editor, Appice, Annalisa, editor, Loglisci, Corrado, editor, Antonie, Luiza, editor, Zimmermann, Albrecht, editor, Guidotti, Riccardo, editor, Özgöbek, Özlem, editor, Ribeiro, Rita P., editor, Gavaldà, Ricard, editor, Gama, João, editor, Adilova, Linara, editor, Krishnamurthy, Yamuna, editor, Ferreira, Pedro M., editor, Malerba, Donato, editor, Medeiros, Ibéria, editor, Ceci, Michelangelo, editor, Manco, Giuseppe, editor, Masciari, Elio, editor, Ras, Zbigniew W., editor, Christen, Peter, editor, Ntoutsi, Eirini, editor, Schubert, Erich, editor, Zimek, Arthur, editor, Monreale, Anna, editor, Biecek, Przemyslaw, editor, Rinzivillo, Salvatore, editor, Kille, Benjamin, editor, Lommatzsch, Andreas, editor, and Gulla, Jon Atle, editor

Published
2020
Full Text
View/download PDF

20. A Cybersecurity Framework for Classifying Non Stationary Data Streams Exploiting Genetic Programming and Ensemble Learning

Author

Folino, Gianluigi, Pisani, Francesco Sergio, Pontieri, Luigi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sergeyev, Yaroslav D., editor, and Kvasov, Dmitri E., editor

Published
2020
Full Text
View/download PDF

23. COVID-19 vaccination and relapse activity:A nationwide cohort study of patients with multiple sclerosis in Denmark

Author

Stastna, Dominika, Elberling, Frederik, Pontieri, Luigi, Framke, Elisabeth, Horakova, Dana, Drahota, Jiri, Nytrova, Petra, Magyari, Melinda, Stastna, Dominika, Elberling, Frederik, Pontieri, Luigi, Framke, Elisabeth, Horakova, Dana, Drahota, Jiri, Nytrova, Petra, and Magyari, Melinda

Abstract

Background and purpose We evaluated whether there was a difference in the occurrence of relapses pre- and post-COVID-19 vaccination in a nationwide cohort of Danish patients with relapsing multiple sclerosis. Methods We conducted a population-based, nationwide cohort study with a cutoff date of 1 October 2022. We used McNemar tests to assess changes in the proportion of patients with recorded relapses within 90 days and 180 days before and after first vaccine dose, and a negative binomial regression model to compare the 90 and 180 days postvaccination annualized relapse rate (ARR) to the 360 days prevaccination ARR. Multivariate Cox regression was used to estimate relapse risk factors. Results We identified 8169 vaccinated (87.3% Comirnaty) patients without a recorded history of a positive COVID-19 test. We did not find statistically significant changes in the proportion of patients with relapses in the 90 days (1.3% vs. 1.4% of patients, p = 0.627) and 180 days (2.7% vs. 2.6% of patients, p = 0.918) pre- and postvaccination. Also, a comparison of the ARR 360 days before (0.064, 95% confidence interval [CI] = 0.058–0.070) with the ARR 90 (0.057, 95% CI = 0.047–0.069, p = 0.285) and 180 (0.055, 95% CI = 0.048–0.063, p = 0.060) days after vaccination did not show statistically significant differences. Lower age, higher Expanded Disability Status Scale score, and relapse within 360 days before vaccination were associated with a higher risk of relapse. Conclusions We did not find evidence of increased relapse activity following the administration of the first dose of the COVID-19 vaccine., Background and purpose: We evaluated whether there was a difference in the occurrence of relapses pre- and post-COVID-19 vaccination in a nationwide cohort of Danish patients with relapsing multiple sclerosis. Methods: We conducted a population-based, nationwide cohort study with a cutoff date of 1 October 2022. We used McNemar tests to assess changes in the proportion of patients with recorded relapses within 90 days and 180 days before and after first vaccine dose, and a negative binomial regression model to compare the 90 and 180 days postvaccination annualized relapse rate (ARR) to the 360 days prevaccination ARR. Multivariate Cox regression was used to estimate relapse risk factors. Results: We identified 8169 vaccinated (87.3% Comirnaty) patients without a recorded history of a positive COVID-19 test. We did not find statistically significant changes in the proportion of patients with relapses in the 90 days (1.3% vs. 1.4% of patients, p = 0.627) and 180 days (2.7% vs. 2.6% of patients, p = 0.918) pre- and postvaccination. Also, a comparison of the ARR 360 days before (0.064, 95% confidence interval [CI] = 0.058–0.070) with the ARR 90 (0.057, 95% CI = 0.047–0.069, p = 0.285) and 180 (0.055, 95% CI = 0.048–0.063, p = 0.060) days after vaccination did not show statistically significant differences. Lower age, higher Expanded Disability Status Scale score, and relapse within 360 days before vaccination were associated with a higher risk of relapse. Conclusions: We did not find evidence of increased relapse activity following the administration of the first dose of the COVID-19 vaccine.

Published
2024

29. Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning

Author

Cuzzocrea, Alfredo, Folino, Francesco, Guarascio, Massimo, Pontieri, Luigi, van der Aalst, Wil, Series Editor, Mylopoulos, John, Series Editor, Rosemann, Michael, Series Editor, Shaw, Michael J., Series Editor, Szyperski, Clemens, Series Editor, Hammoudi, Slimane, editor, Śmiałek, Michał, editor, Camp, Olivier, editor, and Filipe, Joaquim, editor

Published
2018
Full Text
View/download PDF

31. Process Discovery from Low-Level Event Logs

Author

Fazzinga, Bettina, Flesca, Sergio, Furfaro, Filippo, Pontieri, Luigi, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Krogstie, John, editor, and Reijers, Hajo A., editor

Published
2018
Full Text
View/download PDF

32. Combining Model- and Example-Driven Classification to Detect Security Breaches in Activity-Unaware Logs

Author

Fazzinga, Bettina, Folino, Francesco, Furfaro, Filippo, Pontieri, Luigi, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Panetto, Hervé, editor, Debruyne, Christophe, editor, Proper, Henderik A., editor, Ardagna, Claudio Agostino, editor, Roman, Dumitru, editor, and Meersman, Robert, editor

Published
2018
Full Text
View/download PDF

35. COVID‐19 vaccination and relapse activity: A nationwide cohort study of patients with multiple sclerosis in Denmark.

Author

Stastna, Dominika, Elberling, Frederik, Pontieri, Luigi, Framke, Elisabeth, Horakova, Dana, Drahota, Jiri, Nytrova, Petra, and Magyari, Melinda

Subjects
COVID-19 vaccines, MULTIPLE sclerosis, COHORT analysis, DISEASE relapse, DANES
Abstract

Background and purpose: We evaluated whether there was a difference in the occurrence of relapses pre‐ and post‐COVID‐19 vaccination in a nationwide cohort of Danish patients with relapsing multiple sclerosis. Methods: We conducted a population‐based, nationwide cohort study with a cutoff date of 1 October 2022. We used McNemar tests to assess changes in the proportion of patients with recorded relapses within 90 days and 180 days before and after first vaccine dose, and a negative binomial regression model to compare the 90 and 180 days postvaccination annualized relapse rate (ARR) to the 360 days prevaccination ARR. Multivariate Cox regression was used to estimate relapse risk factors. Results: We identified 8169 vaccinated (87.3% Comirnaty) patients without a recorded history of a positive COVID‐19 test. We did not find statistically significant changes in the proportion of patients with relapses in the 90 days (1.3% vs. 1.4% of patients, p = 0.627) and 180 days (2.7% vs. 2.6% of patients, p = 0.918) pre‐ and postvaccination. Also, a comparison of the ARR 360 days before (0.064, 95% confidence interval [CI] = 0.058–0.070) with the ARR 90 (0.057, 95% CI = 0.047–0.069, p = 0.285) and 180 (0.055, 95% CI = 0.048–0.063, p = 0.060) days after vaccination did not show statistically significant differences. Lower age, higher Expanded Disability Status Scale score, and relapse within 360 days before vaccination were associated with a higher risk of relapse. Conclusions: We did not find evidence of increased relapse activity following the administration of the first dose of the COVID‐19 vaccine. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

38. Enhancing Histograms by Tree-Like Bucket Indices

Author

Buccafurri, Francesco, Lax, Gianluca, Sacca', Domenico, Pontieri, Luigi, and Rosaci, Domenico

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Histograms are used to summarize the contents of relations into a number of buckets for the estimation of query result sizes. Several techniques (e.g., MaxDiff and V-Optimal) have been proposed in the past for determining bucket boundaries which provide accurate estimations. However, while search strategies for optimal bucket boundaries are rather sophisticated, no much attention has been paid for estimating queries inside buckets and all of the above techniques adopt naive methods for such an estimation. This paper focuses on the problem of improving the estimation inside a bucket once its boundaries have been fixed. The proposed technique is based on the addition, to each bucket, of 32-bit additional information (organized into a 4-level tree index), storing approximate cumulative frequencies at 7 internal intervals of the bucket. Both theoretical analysis and experimental results show that, among a number of alternative ways to organize the additional information, the 4-level tree index provides the best frequency estimation inside a bucket. The index is later added to two well-known histograms, MaxDiff and V-Optimal, obtaining the non-obvious result that despite the spatial cost of 4LT which reduces the number of allowed buckets once the storage space has been fixed, the original methods are strongly improved in terms of accuracy., Comment: 26 pages, 9 figures

Published
2005

41. A Cloud-Based Prediction Framework for Analyzing Business Process Performances

Author

Cesario, Eugenio, Folino, Francesco, Guarascio, Massimo, Pontieri, Luigi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Buccafurri, Francesco, editor, Holzinger, Andreas, editor, Kieseberg, Peter, editor, Tjoa, A Min, editor, and Weippl, Edgar, editor

Published
2016
Full Text
View/download PDF

42. Classifying Traces of Event Logs on the Basis of Security Risks

Author

Fazzinga, Bettina, Flesca, Sergio, Furfaro, Filippo, Pontieri, Luigi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ceci, Michelangelo, editor, Loglisci, Corrado, editor, Manco, Giuseppe, editor, Masciari, Elio, editor, and Ras, Zbigniew W., editor

Published
2016
Full Text
View/download PDF

46. Mining Multi-variant Process Models from Low-Level Logs

Author

Folino, Francesco, Guarascio, Massimo, Pontieri, Luigi, van der Aalst, Wil, Series editor, Mylopoulos, John, Series editor, Rosemann, Michael, Series editor, Shaw, Michael J., Series editor, Szyperski, Clemens, Series editor, and Abramowicz, Witold, editor

Published
2015
Full Text
View/download PDF

47. A Multi-view Learning Approach to the Discovery of Deviant Process Instances

Author

Cuzzocrea, Alfredo, Folino, Francesco, Guarascio, Massimo, Pontieri, Luigi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Debruyne, Christophe, editor, Panetto, Hervé, editor, Meersman, Robert, editor, Dillon, Tharam, editor, Weichhart, Georg, editor, An, Yuan, editor, and Ardagna, Claudio Agostino, editor

Published
2015
Full Text
View/download PDF

48. A Probabilistic Unified Framework for Event Abstraction and Process Detection from Log Data

Author

Fazzinga, Bettina, Flesca, Sergio, Furfaro, Filippo, Masciari, Elio, Pontieri, Luigi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Debruyne, Christophe, editor, Panetto, Hervé, editor, Meersman, Robert, editor, Dillon, Tharam, editor, Weichhart, Georg, editor, An, Yuan, editor, and Ardagna, Claudio Agostino, editor

Published
2015
Full Text
View/download PDF

49. A Framework Supporting the Analysis of Process Logs Stored in Either Relational or NoSQL DBMSs

Author

Fazzinga, Bettina, Flesca, Sergio, Furfaro, Filippo, Masciari, Elio, Pontieri, Luigi, Pulice, Chiara, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Esposito, Floriana, editor, Pivert, Olivier, editor, Hacid, Mohand-Said, editor, Rás, Zbigniew W., editor, and Ferilli, Stefano, editor

Published
2015
Full Text
View/download PDF

50. Proportion and characteristics of secondary progressive multiple sclerosis in five European registries using objective classifiers

Author

Forsberg, Lars, Spelman, Tim, Klyve, Pernilla, Manouchehrinia, Ali, Ramanujam, Ryan, Mouresan, Elena, Drahota, Jiri, Horakova, Dana, Joensen, Hanna, Pontieri, Luigi, Magyari, Melinda, Ellenberger, David, Stahmann, Alexander, Rodgers, Jeff, Witts, James, Middleton, Rod, Nicholas, Richard, Bezlyak, Vladimir, Adlard, Nicholas, Hach, Thomas, Lines, Carol, Vukusic, Sandra, Soilu-Hanninen, Merja, van der Walt, Anneke, Butzkueven, Helmut, Iaffaldano, Pietro, Trojano, Maria, Glaser, Anna, Hillert, Jan, Forsberg, Lars, Spelman, Tim, Klyve, Pernilla, Manouchehrinia, Ali, Ramanujam, Ryan, Mouresan, Elena, Drahota, Jiri, Horakova, Dana, Joensen, Hanna, Pontieri, Luigi, Magyari, Melinda, Ellenberger, David, Stahmann, Alexander, Rodgers, Jeff, Witts, James, Middleton, Rod, Nicholas, Richard, Bezlyak, Vladimir, Adlard, Nicholas, Hach, Thomas, Lines, Carol, Vukusic, Sandra, Soilu-Hanninen, Merja, van der Walt, Anneke, Butzkueven, Helmut, Iaffaldano, Pietro, Trojano, Maria, Glaser, Anna, and Hillert, Jan

Abstract

BackgroundTo assign a course of secondary progressive multiple sclerosis (MS) (SPMS) may be difficult and the proportion of persons with SPMS varies between reports. An objective method for disease course classification may give a better estimation of the relative proportions of relapsing-remitting MS (RRMS) and SPMS and may identify situations where SPMS is under reported. Materials and methodsData were obtained for 61,900 MS patients from MS registries in the Czech Republic, Denmark, Germany, Sweden, and the United Kingdom (UK), including date of birth, sex, SP conversion year, visits with an Expanded Disability Status Scale (EDSS) score, MS onset and diagnosis date, relapses, and disease-modifying treatment (DMT) use. We included RRMS or SPMS patients with at least one visit between January 2017 and December 2019 if >= 18 years of age. We applied three objective methods: A set of SPMS clinical trial inclusion criteria ("EXPAND criteria") modified for a real-world evidence setting, a modified version of the MSBase algorithm, and a decision tree-based algorithm recently published. ResultsThe clinically assigned proportion of SPMS varied from 8.7% (Czechia) to 34.3% (UK). Objective classifiers estimated the proportion of SPMS from 15.1% (Germany by the EXPAND criteria) to 58.0% (UK by the decision tree method). Due to different requirements of number of EDSS scores, classifiers varied in the proportion they were able to classify; from 18% (UK by the MSBase algorithm) to 100% (the decision tree algorithm for all registries). Objectively classified SPMS patients were older, converted to SPMS later, had higher EDSS at index date and higher EDSS at conversion. More objectively classified SPMS were on DMTs compared to the clinically assigned. ConclusionSPMS appears to be systematically underdiagnosed in MS registries. Reclassified patients were more commonly on DMTs., QC 20230320

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results