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September 11, 2025Journal of Clinical MedicineOpen Access

AI Based Clinical Decision-Making Tool for Neurologists in the Emergency Department

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Authors

AGAlon GorenshteinSFShiri FistelMSMoran Sorka

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Overview

Retrospective analysis shows AI predicts hospital admissions and mortality risk effectively, suggesting improved outcomes for neurologists.

Key Points

  • The AI model predicted hospital admissions with an AUC of 0.88, outperforming expert judgment.
  • Among 1368 emergency department patients, older individuals had higher mortality rates and a greater likelihood of acute stroke.
  • Predictive modeling used a blend of XGBoost and logistic regression for increased accuracy in clinical support.
  • Findings highlight the potential for AI to enhance decision-making, validating a strong correlation with neurologist consensus.

Cite This Study

Gorenshtein et al. (2025) studied this question.

synapsesocial.com/papers/68d43b02713b0b5dfea7b0c5https://doi.org/10.3390/jcm14176333
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Also Consider

Synapse has enriched 2 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1AI vs Human Performance in Conversational Hospital-Based Neurological Diagnosis2025 · 4 citations
  2. 2AI-Based EMG Reporting: A Randomized Controlled Trial2025 · 18 citations