Machine learning for medical image classification DOI Creative Commons
Gulam Mohammed Husain, Jonathan Mayer,

Molly Bekbolatova

et al.

Academia Medicine, Journal Year: 2024, Volume and Issue: 1(4)

Published: Dec. 23, 2024

This review article focuses on the application of machine learning (ML) algorithms in medical image classification. It highlights intricate process involved selecting most suitable ML algorithm for predicting specific conditions, emphasizing critical role real-world data testing and validation. navigates through various methods utilized healthcare, including Supervised Learning, Unsupervised Self-Supervised Deep Neural Networks, Reinforcement Ensemble Methods. The challenge lies not just selection an but identifying appropriate one a task as well, given vast array options available. Each unique dataset requires comparative analysis to determine best-performing algorithm. However, all available is impractical. examines performance recent studies, focusing their applications across different imaging modalities diagnosing conditions. provides summary these offering starting point those seeking select conditions modalities.

Language: Английский

Machine learning for medical image classification DOI Creative Commons
Gulam Mohammed Husain, Jonathan Mayer,

Molly Bekbolatova

et al.

Academia Medicine, Journal Year: 2024, Volume and Issue: 1(4)

Published: Dec. 23, 2024

This review article focuses on the application of machine learning (ML) algorithms in medical image classification. It highlights intricate process involved selecting most suitable ML algorithm for predicting specific conditions, emphasizing critical role real-world data testing and validation. navigates through various methods utilized healthcare, including Supervised Learning, Unsupervised Self-Supervised Deep Neural Networks, Reinforcement Ensemble Methods. The challenge lies not just selection an but identifying appropriate one a task as well, given vast array options available. Each unique dataset requires comparative analysis to determine best-performing algorithm. However, all available is impractical. examines performance recent studies, focusing their applications across different imaging modalities diagnosing conditions. provides summary these offering starting point those seeking select conditions modalities.

Language: Английский

Citations

4