Research map: Evaluation of machine learning pipeline for blood culture outcome prediction on prospectively collected emergency department data
Back to the article
Papers in this map
- The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) · Mervyn Singer · 2016 · 29041 citations · Cited by this paper
- A comparison of routine blood culture methods and multiplex quantitative PCR for detecting pathogens in simulated polymicrobial blood cultures · 2026 · Related
- Definitions for Sepsis and Organ Failure and Guidelines for the Use of Innovative Therapies in Sepsis · Roger C. Bone · 1992 · 13301 citations · Cited by this paper
- Candida glabrata and the host: a neglected affair · 2026 · Related
- C-reactive Protein · Stephen Alan Black · 2004 · 1854 citations · Cited by this paper
- Waddlia chondrophila: from a bovine abortigenic agent to a potential cause of human adverse pregnancy outcomes · 2026 · Related
- Function of C-reactive protein · Terry W. Du Clos · 2000 · 811 citations · Cited by this paper
- Anatomopathological uterine findings of Candida albicans infection in a vulvovaginal model · 2026 · Related
- Contaminant blood cultures and resource utilization. The true consequences of false-positive results · David Westfall Bates · 1991 · 580 citations · Cited by this paper
- Cryptococcus neoformans responds to presence of Mycobacterium by diversifying its morphologies and remodelling its capsular material · 2026 · Related
- Bloodstream infections in critically ill patients: an expert statement · Jean‐François Timsit · 2020 · 477 citations · Cited by this paper
- Temporal genetic changes in human bocavirus 1 in Fukushima, Japan, from 2018 to 2024 · 2026 · Related
- Machine Learning for Antimicrobial Resistance Prediction: Current Practice, Limitations, and Clinical Perspective · Jee In Kim · 2022 · 256 citations · Cited by this paper
- Investigation of the efficacy of high-dose flucloxacillin therapy for borderline oxacillin-resistant (BORSA) Staphylococcus aureus infections of Galleria mellonella larvae · 2026 · Related
- Bloodstream infections – Standard and progress in pathogen diagnostics · Brigitte Lamy · 2019 · 254 citations · Cited by this paper
- Respiratory syncytial virus – from discovery to vaccines · 2026 · Related
- Clinical and economic impact of contaminated blood cultures within the hospital setting · Yaser Masuod Alahmadi · 2011 · 231 citations · Cited by this paper
- Face mask sampling for the detection of microbes in expelled aerosols and the impact of airway clearance on microbial yield in children with cystic fibrosis: a feasibility trial · 2026 · Related
- Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review · Michael Moor · 2021 · 227 citations · Cited by this paper
- Elevated urinary glycosaminoglycans in Staphylococcus aureus bacteraemia with endovascular source · 2026 · Related
- Blood Culture Utilization in the Hospital Setting: a Call for Diagnostic Stewardship · Valeria Fabre · 2021 · 139 citations · Cited by this paper
- Antimicrobial misuse in patients with positive blood cultures · W. Claiborne Dunagan · 1989 · 137 citations · Cited by this paper
- Bloodstream Infections: The peak of the iceberg · Claudio Viscoli · 2016 · 121 citations · Cited by this paper
- Economic health care costs of blood culture contamination: A systematic review · Casey J Dempsey · 2019 · 104 citations · Cited by this paper
- Analysis of strategies to improve cost effectiveness of blood cultures · Oren Zwang · 2006 · 101 citations · Cited by this paper
- Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and outlook · Omar M. Abdeldayem · 2021 · 93 citations · Cited by this paper
- Role of leucocytes cell population data in the early detection of sepsis · Eloísa Urrechaga · 2017 · 67 citations · Cited by this paper
- Mapping the decision pathways of acute infection management in secondary care among UK medical physicians: a qualitative study · Timothy M. Rawson · 2016 · 64 citations · Cited by this paper
- Culture if spikes? Indications and yield of blood cultures in hospitalized medical patients · Katherine D. Linsenmeyer · 2016 · 59 citations · Cited by this paper
- Diagnostic stewardship for blood cultures in the emergency department: A multicenter validation and prospective evaluation of a machine learning prediction tool · Michiel Schinkel · 2022 · 56 citations · Cited by this paper
- Using machine learning to predict blood culture outcomes in the emergency department: a single-centre, retrospective, observational study · Anneroos W. Boerman · 2022 · 42 citations · Cited by this paper
- Prediction of bacteremia at the emergency department during triage and disposition stages using machine learning models · Dong Hyun Choi · 2022 · 33 citations · Cited by this paper
- AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study · Tai‐Han Lin · 2025 · 29 citations · Cited by this paper
- Machine learning of cell population data, complete blood count, and differential count parameters for early prediction of bacteremia among adult patients with suspected bacterial infections and blood culture sampling in emergency departments · Yu-Hsin Chang · 2023 · 28 citations · Cited by this paper
- Applying machine learning algorithms to electronic health records to predict pneumonia after respiratory tract infection · Xiaohui Sun · 2022 · 27 citations · Cited by this paper
- A Machine Learning Predictive Model of Bloodstream Infection in Hospitalized Patients · Rita Murri · 2024 · 23 citations · Cited by this paper
- Cell Population Data NE‐WX, NE‐FSC, LY‐Y of Sysmex XN‐9000 can provide additional information to differentiate macrocytic anaemia from myelodysplastic syndrome: A preliminary study · Daniele Di Luise · 2021 · 22 citations · Cited by this paper
- Real-time artificial intelligence system for bacteremia prediction in adult febrile emergency department patients · Wei-Chun Tsai · 2023 · 22 citations · Cited by this paper
- Embracing cohort heterogeneity in clinical machine learning development: a step toward generalizable models · Michiel Schinkel · 2023 · 20 citations · Cited by this paper
Source: OpenAlex (CC0)