AI vs. traditional scores: which better predicts COVID-19 ICU outcomes?

NCT ID NCT06795880

Completed Knowledge-focused Sponsor: Kocaeli City Hospital Source: ClinicalTrials.gov ↗

First seen Aug 11, 2026 · Last updated Aug 12, 2026 · Updated 1 time

Summary

This study will use artificial intelligence to analyze data from 400 COVID-19 patients treated in intensive care units. The goal is to see if machine learning models, including deep learning, can predict which patients are most likely to die from the disease. The AI's performance will be compared with traditional scoring systems to determine if it offers greater accuracy and reliability. If successful, this approach could help doctors make more informed decisions for critically ill patients.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

What this could lead to: If successful, this could lead to AI tools that help doctors predict which COVID-19 ICU patients are at highest risk, potentially improving care and resource allocation.
What could go wrong: This is a retrospective analysis, not a prospective trial, so results may not apply to future patients. AI models can also be biased or overfit to the data they are trained on, and their accuracy needs validation in real-world settings.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

COVID-19

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

COVID-19

Contacts and locations

Locations

Kocaeli City Hospital

İzmit, Kocaeli, 41060, Turkey (Türkiye)

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