Enhancing Medical Diagnosis Through Deep Learning and Machine Learning Approaches in Image Analysis

被引:0
作者
Usmani, Usman Ahmad [1 ]
Happonen, Ari [2 ]
Watada, Junzo [3 ]
机构
[1] Univ Teknol Petronas, 79 LakeVille, Seri Iskandar 32610, Perak, Malaysia
[2] LUT Univ, Yliopistonkatu 34, Lappeenranta 53850, Finland
[3] 1 Chome 104 Totsukamachi,Shinjuku, Tokyo 1698050, Japan
来源
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023 | 2024年 / 825卷
关键词
Medical diagnosis; Image analysis; Radiology; Pathology; Machine learning; Computer-Aided diagnosis; Deep learning; Artificial intelligence; Imaging modalities; Digitalizatio; Ethical data analysis; Smart society; ARTIFICIAL-INTELLIGENCE;
D O I
10.1007/978-3-031-47718-8_30
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Medical imaging analysis plays a critical role in the medical field, transforming how diseases are found, diagnosed, and treated. The integration of machine learning and deep learning has dramatically advanced the field of medical image analysis, leading to the creation of more advanced algorithms for improved diagnosis and disease detection. This study examines the impact of these cutting-edge technologies on the accuracy of medical imaging analysis. It investigates the most effective algorithms and techniques currently used, as well as how different types of medical images impact the accuracy and efficiency of these algorithms. The limitations and challenges faced during implementation and their effect on healthcare professionals' decision-making are also explored. This research provides a comprehensive understanding of the state of the art in medical image analysis through machine learning and deep learning, highlighting recent developments and their practical applications.
引用
收藏
页码:449 / 468
页数:20
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