PREDICTING OUTCOMES IN MULTIPLE SCLEROSIS THROUGH MACHINE LEARNING USING DATA FROM PHARMACEUTICAL CONSULTATION

被引：0
|
作者：
Cardoso, P. [1 ]
Santos, C. [1 ]
Costa, F. [1 ]
机构：
[1] Luz Saude, Lisbon, Portugal
来源：
VALUE IN HEALTH | 2022年 / 25卷 / 01期
关键词：
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
POSA314
引用
收藏
页码：S200 / S200
页数：1
相关论文
共 50 条
  • [1] Predicting disease severity in multiple sclerosis using multimodal data and machine learning
    Magi Andorra
    Ana Freire
    Irati Zubizarreta
    Nicole Kerlero de Rosbo
    Steffan D. Bos
    Melanie Rinas
    Einar A. Høgestøl
    Sigrid A. de Rodez Benavent
    Tone Berge
    Synne Brune-Ingebretse
    Federico Ivaldi
    Maria Cellerino
    Matteo Pardini
    Gemma Vila
    Irene Pulido-Valdeolivas
    Elena H. Martinez-Lapiscina
    Sara Llufriu
    Albert Saiz
    Yolanda Blanco
    Eloy Martinez-Heras
    Elisabeth Solana
    Priscilla Bäcker-Koduah
    Janina Behrens
    Joseph Kuchling
    Susanna Asseyer
    Michael Scheel
    Claudia Chien
    Hanna Zimmermann
    Seyedamirhosein Motamedi
    Josef Kauer-Bonin
    Alex Brandt
    Julio Saez-Rodriguez
    Leonidas G. Alexopoulos
    Friedemann Paul
    Hanne F. Harbo
    Hengameh Shams
    Jorge Oksenberg
    Antonio Uccelli
    Ricardo Baeza-Yates
    Pablo Villoslada
    Journal of Neurology, 2024, 271 : 1133 - 1149
  • [2] Predicting disease severity in multiple sclerosis using multimodal data and machine learning
    Andorra, Magi
    Freire, Ana
    Zubizarreta, Irati
    de Rosbo, Nicole Kerlero
    Bos, Steffan D.
    Rinas, Melanie
    Hogestol, Einar A.
    Benavent, Sigrid A. de Rodez
    Berge, Tone
    Brune-Ingebretse, Synne
    Ivaldi, Federico
    Cellerino, Maria
    Pardini, Matteo
    Vila, Gemma
    Pulido-Valdeolivas, Irene
    Martinez-Lapiscina, Elena H.
    Llufriu, Sara
    Saiz, Albert
    Blanco, Yolanda
    Martinez-Heras, Eloy
    Solana, Elisabeth
    Baecker-Koduah, Priscilla
    Behrens, Janina
    Kuchling, Joseph
    Asseyer, Susanna
    Scheel, Michael
    Chien, Claudia
    Zimmermann, Hanna
    Motamedi, Seyedamirhosein
    Kauer-Bonin, Josef
    Brandt, Alex
    Saez-Rodriguez, Julio
    Alexopoulos, Leonidas G.
    Paul, Friedemann
    Harbo, Hanne F.
    Shams, Hengameh
    Oksenberg, Jorge
    Uccelli, Antonio
    Baeza-Yates, Ricardo
    Villoslada, Pablo
    JOURNAL OF NEUROLOGY, 2024, 271 (03) : 1133 - 1149
  • [3] Predicting pharmaceutical inkjet printing outcomes using machine learning
    Carou-Senra, Paola
    Ong, Jun Jie
    Castro, Brais Muniz
    Seoane-Viano, Iria
    Rodriguez-Pombo, Lucia
    Cabalar, Pedro
    Alvarez-Lorenzo, Carmen
    Basit, Abdul W.
    Perez, Gilberto
    Goyanes, Alvaro
    INTERNATIONAL JOURNAL OF PHARMACEUTICS-X, 2023, 5
  • [4] Predicting clinical course in multiple sclerosis using machine learning
    Chitnis, T.
    Zhao, Y.
    Healy, B. C.
    Rotstein, D.
    Guttmann, C. R. G.
    Bakshi, R.
    Weiner, H. L.
    Brodley, C. E.
    MULTIPLE SCLEROSIS JOURNAL, 2014, 20 : 404 - 404
  • [5] Predicting Multiple Sclerosis From Gait Dynamics Using an Instrumented Treadmill: A Machine Learning Approach
    Kaur, Rachneet
    Chen, Zizhang
    Motl, Robert
    Hernandez, Manuel E.
    Sowers, Richard
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2021, 68 (09) : 2666 - 2677
  • [6] Predicting falls and injuries in people with multiple sclerosis using machine learning algorithms
    Piryonesi, S. Madeh
    Rostampour, Sorour
    Piryonesi, S. Abdurrahman
    MULTIPLE SCLEROSIS AND RELATED DISORDERS, 2021, 49
  • [7] Multiple Sclerosis Management: Predicting Disease Trajectory Of Multiple Sclerosis On Multi-dimensional Data Including Digital Cognitive Assessments And Patient Reported Outcomes Using Machine Learning Techniques
    Srinivasan, J.
    Gudesblatt, M.
    MULTIPLE SCLEROSIS JOURNAL, 2020, 26 (1_SUPPL) : 99 - 99
  • [8] Predicting multiple sclerosis disease course with patient centred outcomes (PCOs): a machine learning approach
    Brichetto, G.
    Fiorini, S.
    Ponzio, M.
    Barla, A.
    Verri, A.
    Tacchino, A.
    MULTIPLE SCLEROSIS JOURNAL, 2016, 22 : 698 - 698
  • [9] Machine Learning Approaches for Predicting Phenotypes in Pathophysiology of Multiple Sclerosis
    Brandet, Joao M.
    GENETIC EPIDEMIOLOGY, 2021, 45 (07) : 775 - 775
  • [10] Predicting disease course in Multiple Sclerosis using deep learning on clinical data
    Sreenivasan, Akshai Parakkal
    Burman, Joachim
    Kultima, Kim
    Spjuth, Ola
    Vaivade, Aina
    MULTIPLE SCLEROSIS JOURNAL, 2023, 29 : 22 - 22
12345