Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features

<b>Background/Objectives:</b> Despite advances in diagnostic techniques, accurate classification of lung cancer subtypes remains crucial for treatment planning. Traditional methods like genomic studies face limitations such as high cost and complexity. This study investigates whether integrating ato...

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Библиографические подробности

Главные авторы:	Aiga Andrijanova, Lasma Bugovecka, Sergejs Isajevs, Donats Erts, Uldis Malinovskis, Andis Liepins
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2025-01-01
Серии:	Diagnostics
Предметы:	lung cancer cancer subtype classification atomic force microscopy biophysical properties machine learning Bayesian networks
Online-ссылка:	https://www.mdpi.com/2075-4418/15/2/127
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