A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer

被引:10
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
页码:257 / 278
页数:22
相关论文
共 211 条
[1]   The future of artificial intelligence in thoracic surgery for non-small cell lung cancer treatment a narrative review [J].
Abbaker, Namariq ;
Minervini, Fabrizio ;
Guttadauro, Angelo ;
Solli, Piergiorgio ;
Cioffi, Ugo ;
Scarci, Marco .
FRONTIERS IN ONCOLOGY, 2024, 14
[2]  
Abd Al-Ameer AA, 2022, INDONES J ELECT ENG, V28, P987, DOI [DOI 10.11591/IJEECS.V28.I2.PP987-993, 10.11591/ijeecs.v28.i2.pp987-993, 10.11591/IJEECS.V28.I2.PP987-993]
[3]   Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening [J].
Aberle, Denise R. ;
Adams, Amanda M. ;
Berg, Christine D. ;
Black, William C. ;
Clapp, Jonathan D. ;
Fagerstrom, Richard M. ;
Gareen, Ilana F. ;
Gatsonis, Constantine ;
Marcus, Pamela M. ;
Sicks, JoRean D. .
NEW ENGLAND JOURNAL OF MEDICINE, 2011, 365 (05) :395-409
[4]   Assessment of artificial intelligence-aided computed tomography in lung cancer screening [J].
Aboelenin, Noha A. ;
Elserafi, Ahmed ;
Zaki, Noha ;
Rashed, Essam A. ;
al-Shatouri, Mohammad .
EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE, 2023, 54 (01)
[5]   Multisampling-based docking reveals Imidazolidinyl urea as a multitargeted inhibitor for lung cancer: an optimisation followed multi-simulation and in-vitro study [J].
Ahmad, Shaban ;
Singh, Vijay ;
Gautam, Hemant K. K. ;
Raza, Khalid .
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2024, 42 (05) :2494-2511
[6]   Association of IL-6-174G>C and-572G>C Polymorphisms with Risk of Legg-Calve-Perthes Disease in Iranian Children [J].
Akbarian-Bafghi, Mohammad Javad ;
Dastgheib, Seyed Alireza ;
Morovati-Sharifabad, Majid ;
Sobhan, Mohammad Reza ;
Moghimi, Mansour ;
Mahdinezhad-Yazdi, Masoud ;
Lookzadeh, Mohammad Hosein ;
Khajehnoori, Sahel ;
Neamatzadeh, Hossein .
FETAL AND PEDIATRIC PATHOLOGY, 2021, 40 (03) :206-213
[7]   Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer [J].
Alabi, Rasheed Omobolaji ;
Makitie, Antti A. ;
Pirinen, Matti ;
Elmusrati, Mohammed ;
Leivo, Ilmo ;
Almangush, Alhadi .
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2021, 145
[8]   Revolutionizing healthcare: the role of artificial intelligence in clinical practice [J].
Alowais, Shuroug A. ;
Alghamdi, Sahar S. ;
Alsuhebany, Nada ;
Alqahtani, Tariq ;
Alshaya, Abdulrahman I. ;
Almohareb, Sumaya N. ;
Aldairem, Atheer ;
Alrashed, Mohammed ;
Bin Saleh, Khalid ;
Badreldin, Hisham A. ;
Al Yami, Majed S. ;
Al Harbi, Shmeylan ;
Albekairy, Abdulkareem M. .
BMC MEDICAL EDUCATION, 2023, 23 (01)
[9]   A CAD System for Lung Cancer Detection Using Hybrid Deep Learning Techniques [J].
Alsheikhy, Ahmed A. A. ;
Said, Yahia ;
Shawly, Tawfeeq ;
Alzahrani, A. Khuzaim ;
Lahza, Husam .
DIAGNOSTICS, 2023, 13 (06)
[10]   Association of Fetal MTHFR 677C > T Polymorphism with Non-Syndromic Cleft Lip with or without Palate Risk: A Systematic Review and Meta-Analysis [J].
Amooee, Abdolhamid ;
Dastgheib, Seyed Alireza ;
Niktabar, Seyed Mohammadreza ;
Noorishadkam, Mahmood ;
Lookzadeh, Mohamad Hosein ;
Mirjalili, Seyed Reza ;
Heiranizadeh, Naeimeh ;
Neamatzadeh, Hossein .
FETAL AND PEDIATRIC PATHOLOGY, 2021, 40 (04) :337-353