Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees

Due to imbalanced data values and high-dimensional features of lung cancer from CT scans images creates significant challenges in clinical research. The improper classification of these images leads towards higher complexity in classification process. These critical issues compromise the extraction...

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Vydané v:	Scientific reports Ročník 15; číslo 1; s. 18954 - 16
Hlavní autori:	Aswal, Shobha, Ahuja, Neelu Jyothi, Mehra, Ritika
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 29.05.2025 Nature Publishing Group Nature Portfolio
Predmet:	631/114 631/114/1564 Algorithms Binary Bat Swarm Algorithm Biomedical data Cancer Classification Decision making Decision Trees Humanities and Social Sciences Humans Image Processing, Computer-Assisted - methods Imbalanced data Lung cancer Lung Neoplasms - classification Lung Neoplasms - diagnostic imaging Machine Learning multidisciplinary Oblique decision tree Science Science (multidisciplinary) Tomography, X-Ray Computed - methods Imbalanced data Binary Bat Swarm Algorithm Oblique decision tree Lung cancer Biomedical data
ISSN:	2045-2322, 2045-2322
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