A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer

被引:0
|
作者
Haghighikian, Seyed Masoud [1 ]
Shirinzadeh-Dastgiri, Ahmad [2 ]
Vakili-Ojarood, Mohammad [3 ]
Naseri, Amirhosein [4 ]
Barahman, Maedeh [5 ]
Saberi, Ali [1 ]
Rahmani, Amirhossein [6 ]
Shiri, Amirmasoud [7 ]
Masoudi, Ali [8 ]
Aghasipour, Maryam [9 ]
Shahbazi, Amirhossein [10 ]
Ghelmani, Yaser [11 ]
Aghili, Kazem [12 ]
Neamatzadeh, Hossein [13 ]
机构
[1] Iran Univ Med Sci, Hazrat E Rasool Gen Hosp, Sch Med, Dept Gen Surg, Tehran, Iran
[2] Iran Univ Med Sci, Shohadaye Haft E Tir Hosp, Sch Med, Dept Surg, Tehran, Iran
[3] Ardabil Univ Med Sci, Sch Med, Dept Surg, Ardebil, Iran
[4] Aja Univ Med Sci, Imam Reza Hosp, Dept Colorectal Surg, Tehran, Iran
[5] Iran Univ Med Sci IUMS, Firoozgar Hosp, Firoozgar Clin Res Dev Ctr FCRDC, Dept Radiat Oncol, Tehran, Iran
[6] Iranshahr Univ Med Sci, Dept Plast Surg, Iranshahr, Iran
[7] Shiraz Univ Med Sci, Shiraz, Iran
[8] Shahid Sadoughi Univ Med Sci, Yazd, Iran
[9] Univ Cincinnati, Coll Med, Dept Canc Biol, Cincinnati, OH USA
[10] Ilam Univ Med Sci, Student Res Comm, Ilam, Iran
[11] Shahid Sadoughi Univ Med Sci, Clin Res Dev Ctr, Dept Internal Med, Shahid Sadoughi Hosp, Yazd, Iran
[12] Shahid Sadoughi Univ Med Sci, Shahid Rahnamoun Hosp, Sch Med, Dept Radiol, Yazd, Iran
[13] Shahid Sadoughi Univ Med Sci, Mother & Newborn Hlth Res Ctr, Yazd, Iran
关键词
Artificial intelligence; Lung cancer; Deep learning; Machine learning; Adjunct therapy; Convolutional neural networks; NEURAL-NETWORKS; PULMONARY NODULES; CLASSIFICATION; SURVIVAL; MACHINE; VALIDATION; PREDICTION; CT; ALGORITHMS; EXPRESSION;
D O I
10.1007/s13193-024-02079-6
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The application of artificial intelligence (AI) in lung cancer, particularly in surgical approaches, has significantly transformed the healthcare landscape. AI has demonstrated remarkable advancements in early lung cancer detection, precise medical image analysis, and personalized treatment planning, all of which are crucial for surgical interventions. By analyzing extensive datasets, AI algorithms can identify patterns and anomalies in lung scans, facilitating timely diagnoses and enhancing surgical outcomes. Furthermore, AI can detect subtle indicators that may be overlooked by human practitioners, leading to quicker intervention and more effective treatment strategies. The technology can also predict patient responses to surgical treatments, enabling tailored care plans that improve recovery rates. In addition to surgical applications, AI streamlines administrative tasks such as record management and appointment scheduling, allowing healthcare providers to concentrate on delivering high-quality care. The integration of AI with genomics and precision medicine holds the potential to further refine surgical approaches in lung cancer treatment by developing targeted strategies that enhance effectiveness and minimize side effects. Despite challenges related to data privacy and regulatory concerns, the ongoing advancements in AI, coupled with collaboration between healthcare professionals and AI experts, suggest a promising future for lung cancer care. This article explores how AI addresses the challenges of lung cancer treatment, focusing on current advancements, obstacles, and the future potential of surgical applications.
引用
收藏
页数:22
相关论文
共 50 条
  • [1] A holistic approach to implementing artificial intelligence in radiology
    Bomi Kim
    Stephan Romeijn
    Mark van Buchem
    Mohammad Hosein Rezazade Mehrizi
    Willem Grootjans
    [J]. Insights into Imaging, 15
  • [2] A holistic approach to implementing artificial intelligence in radiology
    Kim, Bomi
    Romeijn, Stephan
    van Buchem, Mark
    Mehrizi, Mohammad Hosein Rezazade
    Grootjans, Willem
    [J]. INSIGHTS INTO IMAGING, 2024, 15 (01)
  • [3] Holistic Artificial Intelligence
    Feng, Junlan
    [J]. Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2024, 47 (04): : 1 - 10
  • [4] Implementing artificial intelligence: a generic approach with software support
    Heinimaki, Teemu J.
    Vanhatupa, Juha-Matti
    [J]. PROCEEDINGS OF THE ESTONIAN ACADEMY OF SCIENCES, 2013, 62 (01) : 27 - 38
  • [5] Artificial Intelligence For Air Quality Control Systems: A Holistic Approach
    Bazzi, Tony
    Zohdy, Mohamed
    [J]. 2018 TWENTIETH INTERNATIONAL MIDDLE EAST POWER SYSTEMS CONFERENCE (MEPCON), 2018, : 25 - 32
  • [6] Artificial intelligence: opportunities in lung cancer
    Zhang, Kai
    Chen, Kezhong
    [J]. CURRENT OPINION IN ONCOLOGY, 2022, 34 (01) : 44 - 53
  • [7] Application of Artificial Intelligence in Lung Cancer
    Chiu, Hwa-Yen
    Chao, Heng-Sheng
    Chen, Yuh-Min
    [J]. CANCERS, 2022, 14 (06)
  • [8] Theoretical Approach Of Implementing Blockchain And Artificial Intelligence For Diploma Verification
    Rustemi, Avni
    Atanasovski, Vladimir
    Risteski, Aleksandar
    Idrizi, Florim
    Angelkoska, Valentina
    [J]. 2024 13TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING, MECO 2024, 2024, : 242 - 245
  • [9] Implementing robotics and artificial intelligence
    Sebastian, Sujith
    [J]. ELIFE, 2022, 11
  • [10] Radiomics and artificial intelligence in lung cancer screening
    Binczyk, Franciszek
    Prazuch, Wojciech
    Bozek, Pawel
    Polanska, Joanna
    [J]. TRANSLATIONAL LUNG CANCER RESEARCH, 2021, 10 (02) : 1186 - 1199