Using artificial intelligence and real-world data to identify drugs to repurpose for Parkinson's disease

被引：0
|
作者：
Alford, Sharon Hensley [1 ]
Visanji, Naomi P. [2 ]
Lacoste, Alix M. B. [1 ]
Madan, Piyush [3 ]
Buleje, Italo [4 ]
Han, Yanyan [5 ]
Marras, Connie [2 ]
机构：
[1] IBM Watson Hlth, Cambridge, MA USA
[2] Univ Toronto, Toronto Western Hosp, Toronto, ON, Canada
[3] IBM Res, Cambridge, MA USA
[4] IBM Res, Miami, FL USA
[5] IBM Res, San Jose, CA USA
来源：
PHARMACOEPIDEMIOLOGY AND DRUG SAFETY | 2019年 / 28卷
关键词：
D O I：
暂无
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
263
引用
收藏
页码：131 / 131
页数：1
相关论文
共 50 条
  • [31] Comparing the effectiveness of biological disease-modifying antirheumatic drugs using real-world data
    Takabayashi, Katsuhiko
    Ando, Fumihiko
    Suzuki, Takahiro
    MODERN RHEUMATOLOGY, 2019, 29 (01) : 87 - 97
  • [32] Toward safer ophthalmic artificial intelligence via distributed validation on real-world data
    Nath, Siddharth
    Rahimy, Ehsan
    Kras, Ashley
    Korot, Edward
    CURRENT OPINION IN OPHTHALMOLOGY, 2023, 34 (05) : 459 - 463
  • [33] The future of research in hematology: Integration of conventional studies with real-world data and artificial intelligence
    Passamonti, Francesco
    Corrao, Giovanni
    Castellani, Gastone
    Mora, Barbara
    Maggioni, Giulia
    Gale, Robert Peter
    Della Porta, Matteo Giovanni
    BLOOD REVIEWS, 2022, 54
  • [34] Inventory of real world data sources in Parkinson's disease
    Tanguy, Audrey
    Joensson, Linus
    Ishihara, Lianna
    BMC NEUROLOGY, 2017, 17 : 213
  • [35] Inventory of real world data sources in Parkinson’s disease
    Audrey Tanguy
    Linus Jönsson
    Lianna Ishihara
    BMC Neurology, 17
  • [36] Appendectomy and risk of Parkinson's disease: A meta-analysis using real-world evidence
    Hussain, S.
    Najmi, A.
    MOVEMENT DISORDERS, 2019, 34 : S858 - S859
  • [37] Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review
    Payrovnaziri, Seyedeh Neelufar
    Chen, Zhaoyi
    Rengifo-Moreno, Pablo
    Miller, Tim
    Bian, Jiang
    Chen, Jonathan H.
    Liu, Xiuwen
    He, Zhe
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2020, 27 (07) : 1173 - 1185
  • [38] Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence
    Keyl, Julius
    Keyl, Philipp
    Montavon, Gregoire
    Hosch, Rene
    Brehmer, Alexander
    Mochmann, Liliana
    Jurmeister, Philipp
    Dernbach, Gabriel
    Kim, Moon
    Koitka, Sven
    Bauer, Sebastian
    Bechrakis, Nikolaos
    Forsting, Michael
    Fuehrer-Sakel, Dagmar
    Glas, Martin
    Gruenwald, Viktor
    Hadaschik, Boris
    Haubold, Johannes
    Herrmann, Ken
    Kasper, Stefan
    Kimmig, Rainer
    Lang, Stephan
    Rassaf, Tienush
    Roesch, Alexander
    Schadendorf, Dirk
    Siveke, Jens T.
    Stuschke, Martin
    Sure, Ulrich
    Totzeck, Matthias
    Welt, Anja
    Wiesweg, Marcel
    Baba, Hideo A.
    Nensa, Felix
    Egger, Jan
    Mueller, Klaus-Robert
    Schuler, Martin
    Klauschen, Frederick
    Kleesiek, Jens
    NATURE CANCER, 2025, 6 (02) : 307 - 322
  • [39] Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data
    Liu, Yimeng
    Yu, Ze
    Ye, Xuxiao
    Zhang, Jinyuan
    Hao, Xin
    Gao, Fei
    Yu, Jing
    Zhou, Chunhua
    INTERNATIONAL JOURNAL OF CLINICAL PHARMACY, 2024, 46 (04) : 926 - 936
  • [40] Artificial intelligence for detection of Alzheimer's disease: demonstration of real-world value is required to bridge the translational gap
    Marshall, Charles R.
    Uchegbu, Ijeoma
    LANCET DIGITAL HEALTH, 2022, 4 (11): : E768 - E769
12345