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A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
by Plant, Pamela J , Bains, Manjeet , Haney, Evan E , Nassif, Christina , Tsoporis, James T , Moon, Byeong-Ui , Zhang, Peter G. Y , Da Fonte, Dillon , Marshall, John C , Veres, Teodor , Mounier, Maxence , Churcher, Eryn , Malic, Lidija , Dos Santos, Claudia C , Geissler, Matthias , Hancock, Robert E. W , Trahtemberg, Uriel , Clime, Liviu , Sit, Victor Min-Sung , Brassard, Daniel , Baker, Andrew , Falsafi, Reza , Lukic, Ljuboje
in 38/77 / 38/91 / 49/91 / 631/250/2499 / 631/337/2019 / 631/553 / 692/53/2423 / Aged / Blood / Clinical deterioration / Diagnosis / Emergency medical care / Female / Gene expression / Humanities and Social Sciences / Humans / Immune system / Intensive Care Units / Learning algorithms / Machine Learning / Male / Medical prognosis / Microfluidics / Microfluidics - instrumentation / Microfluidics - methods / Middle Aged / multidisciplinary / Organ Dysfunction Scores / Patients / Point-of-Care Systems / Science / Science (multidisciplinary) / Sensitivity / Sensitivity analysis / Sensitivity and Specificity / Sepsis / Sepsis - blood / Sepsis - diagnosis / Sepsis - genetics
2025
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A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
by Plant, Pamela J , Bains, Manjeet , Haney, Evan E , Nassif, Christina , Tsoporis, James T , Moon, Byeong-Ui , Zhang, Peter G. Y , Da Fonte, Dillon , Marshall, John C , Veres, Teodor , Mounier, Maxence , Churcher, Eryn , Malic, Lidija , Dos Santos, Claudia C , Geissler, Matthias , Hancock, Robert E. W , Trahtemberg, Uriel , Clime, Liviu , Sit, Victor Min-Sung , Brassard, Daniel , Baker, Andrew , Falsafi, Reza , Lukic, Ljuboje
in 38/77 / 38/91 / 49/91 / 631/250/2499 / 631/337/2019 / 631/553 / 692/53/2423 / Aged / Blood / Clinical deterioration / Diagnosis / Emergency medical care / Female / Gene expression / Humanities and Social Sciences / Humans / Immune system / Intensive Care Units / Learning algorithms / Machine Learning / Male / Medical prognosis / Microfluidics / Microfluidics - instrumentation / Microfluidics - methods / Middle Aged / multidisciplinary / Organ Dysfunction Scores / Patients / Point-of-Care Systems / Science / Science (multidisciplinary) / Sensitivity / Sensitivity analysis / Sensitivity and Specificity / Sepsis / Sepsis - blood / Sepsis - diagnosis / Sepsis - genetics
2025
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A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
by Plant, Pamela J , Bains, Manjeet , Haney, Evan E , Nassif, Christina , Tsoporis, James T , Moon, Byeong-Ui , Zhang, Peter G. Y , Da Fonte, Dillon , Marshall, John C , Veres, Teodor , Mounier, Maxence , Churcher, Eryn , Malic, Lidija , Dos Santos, Claudia C , Geissler, Matthias , Hancock, Robert E. W , Trahtemberg, Uriel , Clime, Liviu , Sit, Victor Min-Sung , Brassard, Daniel , Baker, Andrew , Falsafi, Reza , Lukic, Ljuboje
in 38/77 / 38/91 / 49/91 / 631/250/2499 / 631/337/2019 / 631/553 / 692/53/2423 / Aged / Blood / Clinical deterioration / Diagnosis / Emergency medical care / Female / Gene expression / Humanities and Social Sciences / Humans / Immune system / Intensive Care Units / Learning algorithms / Machine Learning / Male / Medical prognosis / Microfluidics / Microfluidics - instrumentation / Microfluidics - methods / Middle Aged / multidisciplinary / Organ Dysfunction Scores / Patients / Point-of-Care Systems / Science / Science (multidisciplinary) / Sensitivity / Sensitivity analysis / Sensitivity and Specificity / Sepsis / Sepsis - blood / Sepsis - diagnosis / Sepsis - genetics
2025

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A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis
Journal Article

A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis

Plant, Pamela J,
Bains, Manjeet,
Haney, Evan E,
Nassif, Christina,
Tsoporis, James T,
Moon, Byeong-Ui,
Zhang, Peter G. Y,
Da Fonte, Dillon,
Marshall, John C,
Veres, Teodor,
Mounier, Maxence,
Churcher, Eryn,
Malic, Lidija,
Dos Santos, Claudia C,
Geissler, Matthias,
Hancock, Robert E. W,
Trahtemberg, Uriel,
Clime, Liviu,
Sit, Victor Min-Sung,
Brassard, Daniel,
Baker, Andrew,
Falsafi, Reza,
Lukic, Ljuboje
2025
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NRC publication: Yes
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Publisher
Nature,Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject

38/77

/ 38/91

/ 49/91

/ 631/250/2499

/ 631/337/2019

/ 631/553

/ 692/53/2423

/ Aged

/ Blood

/ Clinical deterioration

/ Diagnosis

/ Emergency medical care

/ Female

/ Gene expression

/ Humanities and Social Sciences

/ Humans

/ Immune system

/ Intensive Care Units

/ Learning algorithms

/ Machine Learning

/ Male

/ Medical prognosis

/ Microfluidics

/ Microfluidics - instrumentation

/ Microfluidics - methods

/ Middle Aged

/ multidisciplinary

/ Organ Dysfunction Scores

/ Patients

/ Point-of-Care Systems

/ Science

/ Science (multidisciplinary)

/ Sensitivity

/ Sensitivity analysis

/ Sensitivity and Specificity

/ Sepsis

/ Sepsis - blood

/ Sepsis - diagnosis

/ Sepsis - genetics

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