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
相关论文
共 50 条
  • [1] Deep Learning Approaches for Medical Image Analysis and Diagnosis
    Thakur, Gopal Kumar
    Thakur, Abhishek
    Kulkarni, Shridhar
    Khan, Naseebia
    Khan, Shahnawaz
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2024, 16 (05)
  • [2] Deep Learning in Medical Image Analysis
    Chan, Heang-Ping
    Samala, Ravi K.
    Hadjiiski, Lubomir M.
    Zhou, Chuan
    DEEP LEARNING IN MEDICAL IMAGE ANALYSIS: CHALLENGES AND APPLICATIONS, 2020, 1213 : 3 - 21
  • [3] Machine learning and deep learning approach for medical image analysis: diagnosis to detection
    Rana, Meghavi
    Bhushan, Megha
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (17) : 26731 - 26769
  • [4] Machine learning and deep learning approach for medical image analysis: diagnosis to detection
    Meghavi Rana
    Megha Bhushan
    Multimedia Tools and Applications, 2023, 82 : 26731 - 26769
  • [5] Machine learning approaches in medical image analysis: From detection to diagnosis
    de Bruijne, Marleen
    MEDICAL IMAGE ANALYSIS, 2016, 33 : 94 - 97
  • [6] Cancer Detection Based on Medical Image Analysis with the Help of Machine Learning and Deep Learning Techniques: A Systematic Literature Review
    Sood, Tamanna
    Bhatia, Rajesh
    Khandnor, Padmavati
    CURRENT MEDICAL IMAGING, 2023, 19 (13) : 1487 - 1522
  • [7] Machine learning and deep learning approaches in IoT
    Javed A.
    Awais M.
    Shoaib M.
    Khurshid K.S.
    Othman M.
    PeerJ Computer Science, 2023, 9
  • [8] Deep learning models in medical image analysis
    Tsuneki, Masayuki
    JOURNAL OF ORAL BIOSCIENCES, 2022, 64 (03) : 312 - 320
  • [9] Review of Machine Learning and Deep Learning Techniques for Medical Image Analysis
    Saratkar, Saniya
    Raut, Rohini
    Thute, Trupti
    Chaudhari, Aarti
    Thakre, Gaitri
    2024 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT CYBER PHYSICAL SYSTEMS AND INTERNET OF THINGS, ICOICI 2024, 2024, : 1437 - 1443
  • [10] Deep Learning for Image Analysis in the Diagnosis and Management of Esophageal Cancer
    Theocharopoulos, Charalampos
    Davakis, Spyridon
    Ziogas, Dimitrios C.
    Theocharopoulos, Achilleas
    Foteinou, Dimitra
    Mylonakis, Adam
    Katsaros, Ioannis
    Gogas, Helen
    Charalabopoulos, Alexandros
    CANCERS, 2024, 16 (19)