Standard

The secrets of sepsis : A data-driven approach to improve its diagnostic work-up and treatment. / Schinkel, M.

2023. 270 p.

Research output: PhD Thesis › Phd-Thesis - Research and graduation internal

Harvard

Schinkel, M 2023, 'The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment', Doctor of Philosophy, University of Amsterdam. <https://hdl.handle.net/11245.1/83a05a03-d32b-47d5-9870-4385c39fbf9a>

APA

Schinkel, M. (2023). The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment. [Phd-Thesis - Research and graduation internal, University of Amsterdam].

Vancouver

Schinkel M. The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment. 2023. 270 p.

Author

Schinkel, M.. / The secrets of sepsis : A data-driven approach to improve its diagnostic work-up and treatment. 2023. 270 p.

BibTeX

@phdthesis{444002ef238c4bc28da41aed9a38b8e4,
title = "The secrets of sepsis: A data-driven approach to improve its diagnostic work-up and treatment",
abstract = "This thesis investigates sepsis management, focusing on diagnostic work-up, antibiotic treatment, and applying data and machine learning to optimize care. Despite decades of research, effective sepsis-specific therapies have yet to be found, limiting the treatment options to supportive therapy and antimicrobials. By implementing a sepsis response team in our hospital's emergency",
author = "M. Schinkel",
year = "2023",
month = may,
day = "26",
language = "English",
isbn = "9789493278431",
school = "University of Amsterdam",

}

RIS

TY - THES

T1 - The secrets of sepsis

T2 - A data-driven approach to improve its diagnostic work-up and treatment

AU - Schinkel, M.

PY - 2023/5/26

Y1 - 2023/5/26

N2 - This thesis investigates sepsis management, focusing on diagnostic work-up, antibiotic treatment, and applying data and machine learning to optimize care. Despite decades of research, effective sepsis-specific therapies have yet to be found, limiting the treatment options to supportive therapy and antimicrobials. By implementing a sepsis response team in our hospital's emergency

AB - This thesis investigates sepsis management, focusing on diagnostic work-up, antibiotic treatment, and applying data and machine learning to optimize care. Despite decades of research, effective sepsis-specific therapies have yet to be found, limiting the treatment options to supportive therapy and antimicrobials. By implementing a sepsis response team in our hospital's emergency

M3 - Phd-Thesis - Research and graduation internal

SN - 9789493278431

ER -

ID: 38324163