Data science in healthcare: Benefits, challenges and opportunities

Autor: Abedjan, Ziawasch, Boujemaa, Nozha, Campbell, Stuart, Casla, Patricia, Chatterjea, Supriyo, Consoli, Sergio, Costa-Soria, Cristobal, Czech, Paul, Despenic, Marija, Garattini, Chiara, Hamelinck, Dirk, Heinrich, Adrienne, Kraaij, Wessel, Kustra, Jacek, Lojo, Aizea, Sanchez, Marga Martin, Mayer, Miguel A., Melideo, Matteo, Menasalvas, Ernestina, Aarestrup, Frank Moller, Artigot, Elvira Narro, Petković, Milan, Recupero, Diego Reforgiato, Gonzalez, Alejandro Rodriguez, Kerremans, Gisele Roesems, Roller, Roland, Romao, Mario, Ruping, Stefan, Sasaki, Felix, Spek, Wouter, Stojanovic, Nenad, Thoms, Jack, Vasiljevs, Andrejs, Verachtert, Wilfried, Wuyts, Roel, Consoli, S., Reforgiato Recupero, D., Petković, M.

Publikováno v: Data Science for Healthcare: Methodologies and Applications, 3-38
Data Science for Healthcare ISBN: 9783030052485
Data Science for Healthcare
Data Science for Healthcare-Methodologies and Applications
STARTPAGE=3;ENDPAGE=38;TITLE=Data Science for Healthcare

The advent of digital medical data has brought an exponential increase in information available for each patient, allowing for novel knowledge generation methods to emerge. Tapping into this data brings clinical research and clinical practice closer

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