The Opportunities and Challenges for Artificial Intelligence to Improve Sepsis Outcomes in the Paediatric Intensive Care Unit

Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework

(2023) Anton H van der Vegt et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

Tackling Neonatal Sepsis—Can It Be Predicted?

(2023) Špela But et al.   International Journal of Environmental Research and Public Health

Publisher Correction: Large language models encode clinical knowledge

(2023) Karan Singhal et al.   NATURE

AI in health and medicine

(2022) Pranav Rajpurkar et al.   NATURE MEDICINE

Neonatal sepsis: a systematic review of core outcomes from randomised clinical trials

(2022) Cían J. Henry et al.   PEDIATRIC RESEARCH

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

(2022) Baptiste Vasey et al.   NATURE MEDICINE

Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis

(2022) Roy Adams et al.   NATURE MEDICINE

Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing

(2022) Katharine E. Henry et al.   NATURE MEDICINE

Mortality Prediction in Sepsis With an Immune-Related Transcriptomics Signature: A Multi-Cohort Analysis

(2022) Louis Kreitmann et al.   Frontiers in Medicine

Utilizing big data from electronic health records in pediatric clinical care

(2022) Charles G. Macias et al.   PEDIATRIC RESEARCH

Newborn Cry-Based Diagnostic System to Distinguish between Sepsis and Respiratory Distress Syndrome Using Combined Acoustic Features

(2022) Zahra Khalilzad et al.   Diagnostics

Intelligent Neonatal Sepsis Early Diagnosis System for Very Low Birth Weight Infants

(2021) Fabio Tarricone et al.   Applied Sciences-Basel

Continuous Prediction of Mortality in the PICU

(2021) Melissa D. Aczon et al.   Pediatric Critical Care Medicine

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission

(2021) Shayantan Banerjee et al.   Frontiers in Immunology

Safety-driven design of machine learning for sepsis treatment

(2021) Yan Jia et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis

(2021) Martin Stocker et al.   PEDIATRIC INFECTIOUS DISEASE JOURNAL

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence

(2021) Gary S Collins et al.   BMJ Open

The Epic Sepsis Model Falls Short—The Importance of External Validation

(2021) Anand R. Habib et al.   JAMA Internal Medicine

Explanation of machine learning models using shapley additive explanation and application for real data in hospital

(2021) Yasunobu Nohara et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Criteria for Pediatric Sepsis—A Systematic Review and Meta-Analysis by the Pediatric Sepsis Definition Taskforce*

(2021) Kusum Menon et al.   CRITICAL CARE MEDICINE

Achieving Diagnostic Excellence for Sepsis

(2021) Derek C. Angus et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Neonatal sepsis definitions from randomised clinical trials

(2021) Rían Hayes et al.   PEDIATRIC RESEARCH

Gram-negative neonatal sepsis in low- and lower-middle-income countries and WHO empirical antibiotic recommendations: A systematic review and meta-analysis

(2021) Sophie C. H. Wen et al.   PLOS MEDICINE

Diagnostic Challenges in Sepsis

(2021) Chris F. Duncan et al.   Current Infectious Disease Reports

Combating Childhood Infections in LMICs: evaluating the contribution of Big Data Big data, biomarkers and proteomics: informing childhood diarrhoeal disease management in Low- and Middle-Income Countries

(2021) Karen H. Keddy et al.   EBioMedicine

The epidemiology of sepsis in paediatric intensive care units in Brazil (the Sepsis PREvalence Assessment Database in Pediatric population, SPREAD PED): an observational study

(2021) Daniela Carla de Souza et al.   Lancet Child & Adolescent Health

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy

(2020) Lucas M. Fleuren et al.   INTENSIVE CARE MEDICINE

Surviving sepsis campaign international guidelines for the management of septic shock and sepsis-associated organ dysfunction in children

(2020) Scott L. Weiss et al.   INTENSIVE CARE MEDICINE

Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study

(2020) Kristina E Rudd et al.   LANCET

A Deep Learning Approach to Antibiotic Discovery

(2020) Jonathan M. Stokes et al.   CELL

Species Identification and Antibiotic Resistance Prediction by Analysis of Whole Genome Sequence Data Using ARESdb – An Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial

(2020) Ines Ferreira et al.   JOURNAL OF CLINICAL MICROBIOLOGY

Human–computer collaboration for skin cancer recognition

(2020) Philipp Tschandl et al.   NATURE MEDICINE

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer

(2020) Dejun Zhou et al.   Nature Communications

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study

(2020) Mark P Sendak et al.   JMIR Medical Informatics

Machine learning based refined differential gene expression analysis of pediatric sepsis

(2020) Mostafa Abbas et al.   BMC Medical Genomics

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

(2020) Xiaoxuan Liu et al.   NATURE MEDICINE

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension

(2020) Samantha Cruz Rivera et al.   BMJ-British Medical Journal

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension

(2020) Xiaoxuan Liu et al.   BMJ-British Medical Journal

Cost-effectiveness of Autonomous Point-of-Care Diabetic Retinopathy Screening for Pediatric Patients With Diabetes

(2020) Risa M. Wolf et al.   JAMA Ophthalmology

Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study

(2020) Sahil Sandhu et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis

(2019) Christopher W. Seymour et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Utilisation of Electronic Health Records for Public Health in Asia: A Review of Success Factors and Potential Challenges

(2019) Lesley Dornan et al.   Biomed Research International

Do no harm: a roadmap for responsible machine learning for health care

(2019) Jenna Wiens et al.   NATURE MEDICINE

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis

(2019) Po-Hsuan Cameron Chen et al.   NATURE MEDICINE

Key challenges for delivering clinical impact with artificial intelligence

(2019) Christopher J. Kelly et al.   BMC Medicine

Potential Liability for Physicians Using Artificial Intelligence

(2019) W. Nicholson Price et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Development and Validation of a Predictive Model of the Risk of Pediatric Septic Shock Using Data Known at the Time of Hospital Arrival

(2019) Halden F. Scott et al.   JOURNAL OF PEDIATRICS

Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms

(2018) Florian Lamping et al.   BMC Pediatrics

Technological Distractions (Part 2)

(2018) Bradford D. Winters et al.   CRITICAL CARE MEDICINE

What is the safety case for health IT? A study of assurance practices in England

(2018) Ibrahim Habli et al.   SAFETY SCIENCE

Learning from class-imbalanced data: Review of methods and applications

(2017) Guo Haixiang et al.   EXPERT SYSTEMS WITH APPLICATIONS

Diagnostic Test Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children

(2016) Jethro A. Herberg et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)

(2016) Mervyn Singer et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Pattern discovery in critical alarms originating from neonates under intensive care

(2016) Rohan Joshi et al.   PHYSIOLOGICAL MEASUREMENT

Big data in global health: improving health in low- and middle-income countries

(2015) Rosemary Wyber et al.   BULLETIN OF THE WORLD HEALTH ORGANIZATION

Addressing Global Data Sharing Challenges

(2015) George C. Alter et al.   Journal of Empirical Research on Human Research Ethics

Validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) Screening for Sepsis in Surgical Mortalities

(2014) Rajesh Ramanathan et al.   Surgical Infections

Surviving Sepsis Campaign: International Guidelines for Management of Severe Sepsis and Septic Shock, 2012

(2013) R. P. Dellinger et al.   INTENSIVE CARE MEDICINE

Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: diagnostic study

(2013) R. G. Nijman et al.   BMJ-British Medical Journal

Identifying Patients With Severe Sepsis Using Administrative Claims

(2012) Theodore J. Iwashyna et al.   MEDICAL CARE

The Era of Molecular and Other Non-Culture-Based Methods in Diagnosis of Sepsis

(2010) N. Mancini et al.   CLINICAL MICROBIOLOGY REVIEWS

Diagnostic value of clinical features at presentation to identify serious infection in children in developed countries: a systematic review

(2010) Ann Van den Bruel et al.   LANCET

Identification of pediatric septic shock subclasses based on genome-wide expression profiling

(2009) Hector R Wong et al.   BMC Medicine

Genomic expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum*

(2009) Hector R. Wong et al.   CRITICAL CARE MEDICINE