Unsupervised Clustering Successfully Predicts Prognosis in NSCLC Brain Metastasis Cohorts

Unsupervised Clustering Successfully Predicts Prognosis in NSCLC Brain Metastasis Cohorts

<b>Background/Objectives</b>: Current developments in computer-aided systems rely heavily on complex and computationally intensive algorithms. However, even a simple approach can offer a promising solution to reduce the burden on clinicians. Addressing this, we aim to employ unsupervised...

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Bibliographic Details
Main Authors: Emre Uysal, Gorkem Durak, Ayse Kotek Sedef, Ulas Bagci, Tanju Berber, Necla Gurdal, Berna Akkus Yildirim
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Diagnostics
Subjects:
brain metastases
non-small-cell lung cancer
prognostic factors
unsupervised learning
clustering
Online Access:https://www.mdpi.com/2075-4418/15/14/1747
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