⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

April 9, 2024Neurology

Functional Prognostication of Patients Receiving Thrombolytics in Acute Ischemic Stroke with Machine Learning (S6.005)

Luis Silva Shayan Khan Solmaz Ramezani Hashtjin Karen Shabano Stalin Durairaj Saketh Annam Abbey Staugaitis Christopher Streib

View at Publisher

Ask AI

Bookmark

Share

Abstract

To test whether a Neural Network (NN) algorithm could accurately predict long-term neurological outcomes for Acute Ischemic Stroke (AIS) patients receiving intravenous thrombolysis using common clinical variables.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Silva et al. (2024) studied this question.

synapsesocial.com/papers/68e6fdb8b6db643587678161 https://doi.org/10.1212/wnl.0000000000206602

View at Publisher

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Machine learning-based prediction of early neurological deterioration after intravenous thrombolysis for stroke: insights from a large multicenter study2024 · 7 citations
2Predicting prognosis in patients with stroke treated with intravenous alteplase through blood pressure changes: A machine learning‐based approachcohort · 2023 · 9 citations
3Explainable machine learning model for predicting the outcome of acute ischemic stroke after intravenous thrombolysis2025 · 4 citations
4Machine learning is an effective method to predict the 3-month prognosis of patients with acute ischemic stroke2024 · 5 citations
5A Transparent AI Model for Predicting Post-Thrombolytic Outcomes in Acute Ischemic Stroke Patients2025