Machine leanring for predicting caccine immunogenicity
Year of publication: |
September-October 2016
|
---|---|
Authors: | Lee, Eva K. ; Nakaya, Helder I. ; Yuan, Fan ; Querec, Troy D. ; Burel, Greg ; Pietz, Ferdinand H. ; Benecke, Bernard A. ; Pulendran, Bali |
Published in: |
Interfaces : the INFORMS journal on the practice of operations research. - Catonsville, MD : INFORMS, ISSN 0092-2102, ZDB-ID 120785-4. - Vol. 46.2016, 5, p. 368-390
|
Subject: | machine learning | multiple-group classification | vaccine immunogenicity prediction | influenza | yellow fever | malaria | health security | prophylactic medical countermeasures | hypothesis generation | vaccine design for emerging infections | Künstliche Intelligenz | Artificial intelligence | Impfung | Vaccination | Infektionskrankheit | Infectious disease | Prognoseverfahren | Forecasting model | Tropenkrankheit | Tropical disease | Arzneimittel | Pharmaceuticals | Gesundheitsvorsorge | Preventive care | Gesundheitspolitik | Health policy | Epidemie | Epidemic |
-
COVID-19 : prediction, prevalence, and the operations of vaccine allocation
Bennouna, Amine, (2023)
-
Data-driven COVID-19 vaccine development for Janssen
Bertsimas, Dimitris, (2023)
-
Modern infectious diseases: macroeconomic impacts and policy responses
Bloom, David E., (2020)
- More ...
-
Vaccine prioritization for effective pandemic response
Lee, Eva K., (2015)
-
Advancing public health and medical preparedness with operations research
Lee, Eva K., (2013)
-
Advancing Public Health and Medical Preparedness with Operations Research
Lee, Eva K., (2013)
- More ...