ArticleInternational journal of emergency medicine2023
The impact on clinical outcomes after 1 year of implementation of an artificial intelligence solution for the detection of intracranial hemorrhage.
Article in International journal of emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.
- Systematic review of commercial artificial intelligence tools for the detection and volume quantification in intracerebral hemorrhage.European radiology · 2026Pooled it
- Systematic review on the impact of deep learning-driven worklist triage on radiology workflow and clinical outcomes.European radiology · 2025Pooled it
- Towards Explainability in Deep Learning for Detection of Five Major Intracranial Hemorrhage Subtypes on Head CT Using Multi-window DICOM Imaging and Patient-Level Cross-Validation.Journal of imaging informatics in medicine · 2026Article
- Diagnostic Accuracy and Time Efficiency of Artificial Intelligence for Intracranial Hemorrhage Detection on Emergency Brain CT.Diagnostics (Basel, Switzerland) · 2026Article
- AI assistance improves radiology resident reader performance in CT diagnosis of intracranial hemorrhage.La Radiologia medica · 2026Article
- Advancements in smart healthcare in emergency trauma care: from intelligent triage to prognostic prediction.Frontiers in public health · 2026Review
- Performance Comparison Between Two Versions of a Commercial Artificial Intelligence System for Chest Radiograph Interpretation: A Multicenter Study.Journal of imaging informatics in medicine · 2025Article
- Impact of a computed tomography-based artificial intelligence software on radiologists' workflow for detecting acute intracranial hemorrhage.Diagnostic and interventional radiology (Ankara, Turkey) · 2025Article
- AI-driven healthcare innovations for enhancing clinical services during mass gatherings (Hajj): task force insights and future directions.BMC health services research · 2025Article
- An Artificial Intelligence Algorithm Integrated into the Clinical Workflow Can Ensure High Quality Acute Intracranial Hemorrhage CT Diagnostic.Clinical neuroradiology · 2025Article
- The Role of Artificial Intelligence in Triaging Patients in Eye Casualty Departments: A Systematic Review.Cureus · 2025Review
- Article
- Artificial Intelligence as A Complementary Tool for Clincal Decision-Making in Stroke and Epilepsy.Brain sciences · 2024Review
- Optimization of Radiology Diagnostic Services for Patients with Stroke in Multidisciplinary Hospitals.Materia socio-medica · 2024Review
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo assess the effect of a commercial artificial intelligence (AI) solution implementation in the emergency department on clinical outcomes in a single level 1 trauma center.
methodsA retrospective cohort study for two time periods-pre-AI (1.1.2017-1.1.2018) and post-AI (1.1.2019-1.1.2020)-in a level 1 trauma center was performed. The ICH algorithm was applied to 587 consecutive patients with a confirmed diagnosis of ICH on head CT upon admission to the emergency department. Study variables included demographics, patient outcomes, and imaging data. Participants admitted to the emergency department during the same time periods for other acute diagnoses (ischemic stroke (IS) and myocardial infarction (MI)) served as control groups. Primary outcomes were 30- and 120-day all-cause mortality. The secondary outcome was morbidity based on Modified Rankin Scale for Neurologic Disability (mRS) at discharge.
resultsFive hundred eighty-seven participants (289 pre-AI-age 71 ± 1, 169 men; 298 post-AI-age 69 ± 1, 187 men) with ICH were eligible for the analyzed period. Demographics, comorbidities, Emergency Severity Score, type of ICH, and length of stay were not significantly different between the two time periods. The 30- and 120-day all-cause mortality were significantly reduced in the post-AI group when compared to the pre-AI group (27.7% vs 17.5%; p = 0.004 and 31.8% vs 21.7%; p = 0.017, respectively). Modified Rankin Scale (mRS) at discharge was significantly reduced post-AI implementation (3.2 vs 2.8; p = 0.044).
conclusionThe added value of this study emphasizes the introduction of artificial intelligence (AI) computer-aided triage and prioritization software in an emergent care setting that demonstrated a significant reduction in a 30- and 120-day all-cause mortality and morbidity for patients diagnosed with intracranial hemorrhage (ICH). Along with mortality rates, the AI software was associated with a significant reduction in the Modified Ranking Scale (mRs).
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