Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology

Martín Noguerol, Teodoro, Paulano-Godino, Félix, Martín-Valdivia, María Teresa, Menias, Christine O., Luna, Antonio·2019·Journal of the American College of Radiology

Cited by (175)

Items 101–175 of 175

  1. CT, MRI, and radiomics studies of liver metastasis histopathological growth patterns: an up-to-date review
    Shenglin Li, Zhengxiao Li, Xiaoyu Huang, Peng Zhang, Juan Deng, Xianwang Liu, Caiqiang Xue, Wenjuan Zhang, Junlin Zhou · 2022 · Abdominal Radiology
  2. Manual data labeling, radiology, and artificial intelligence: It is a dirty job, but someone has to do it
    Teodoro Martín‐Noguerol, Pilar López Úbeda, Félix Paulano‐Godino, Antonio Luna · 2024 · Magnetic Resonance Imaging
  3. Extracellular volume fraction can predict the treatment response and survival outcome of colorectal cancer liver metastases
    Shenglin Li, Xinmei Yang, Ting Lu, Long Yuan, Yuting Zhang, Jun Zhao, Juan Deng, Caiqiang Xue, Qiu Sun, Xianwang Liu et al. · 2024 · European Journal of Radiology
  4. Segmentation of the nasopalatine canal and detection of canal furcation status with artificial intelligence on cone-beam computed tomography images
    Hatice Ahsen DENİZ, İbrahim Şevki Bayrakdar, Rana Nalçacı, Kaan Orhan · 2025 · Oral Radiology
  5. New insights into the evaluation of peripheral nerves lesions: a survival guide for beginners
    Teodoro Martín‐Noguerol, Rafael Barousse, Antonio Luna, Mariano Socolovsky, J. M. Górriz, Manuel María Gómez-Río · 2022 · Neuroradiology
  6. Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler images
    Han Liu, Chunjie Hou, Jinglan Tang, Li-Tao Sun, Ke‐Feng Lu, Ying Liu, Pei Du · 2023 · Scientific Reports
  7. Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage
    Lingxu Chen, Xiaochen Wang, Sihui Wang, Xuening Zhao, Ying Yan, Mengyuan Yuan, Shengjun Sun · 2025 · BMC Medical Imaging
  8. Triage and workflow optimization with artificial intelligence in pediatric imaging
    Harsimran Bhatia, Anmol Bhatia, Arhanjit Singh, Shubham Saini, Kushaljit Singh Sodhi · 2025 · Pediatric Radiology
  9. “First, do no harm” in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence- A systematic literature review
    Margarida Mateus, Irina Alho, Ana Luísa Neves, Henrique Ferreira Marques Lopes, Mónica Maria Bessa Correia · 2026 · BMC Medical Ethics
  10. Early-Stage Cervical Cancer Detection via Ensemble Learning and Image Feature Integration
    Lalasa Mukku, Jyothi Thomas · 2024 · Lecture notes in networks and systems
  11. Machine Learning-Based Model Helps to Decide which Patients May Benefit from Pancreatoduodenectomy
    Emanuel Vigia, Luís Ramalhete, Edite Filipe, Luís Bicho, Ana Marta Nobre, Paulo Mira, Maria Macedo, Catarina Aguiar, Sofia Costa Corado, Beatriz Chumbinho et al. · 2023 · Onco
  12. A Glimpse on Trends and Characteristics of Recent Articles Published in the Korean Journal of Radiology
    Yeon Hyeon Choe · 2019 · Korean Journal of Radiology
  13. Large language models in Radiology: The importance of fine-tuning and the fable of the luthier
    Teodoro Martín‐Noguerol, Pilar López Úbeda, Antonio Luna · 2024 · European Journal of Radiology
  14. The perils of modern telemetry: A human factors perspective
    Jenna M. Korentsides, Zander N. Miller, Elizabeth Hunter Lazzara, Rosemarie Fernandez, Joseph Roland Keebler · 2025 · Human Factors in Healthcare
  15. Bias in Artificial Intelligence: Impact on Breast Imaging
    Jose Net, Fernando Collado‐Mesa · 2025 · Journal of Breast Imaging
  16. [Retracted] Corporate Marketing Strategy Analysis with Machine Learning Algorithms
    Haoran Nan, Min Hu · 2022 · Wireless Communications and Mobile Computing · Retracted
  17. A fluorescence based dual sensor for Zn 2+ and PO 4 3− and the application of soft computing methods to predict machine learning outcomes
    Shashanka Shekhar Samanta, Subhadip Giri, Sourav Mandal, Usha Mandal, Hasibul Beg, Ajay Misra · 2024 · Physical Chemistry Chemical Physics
  18. The application of machine learning to imaging in hematological oncology: A scoping review
    Stylianos Kotsyfakis, Evangelia Iliaki-Giannakoudaki, Antonios Anagnostopoulos, Eleni Papadokostaki, Konstantinos Giannakoudakis, Michail Goumenakis, Michail Kotsyfakis · 2022 · Frontiers in Oncology
  19. Deep learning based Glaucoma Network Classification ( GNC ) using retinal images
    Iqra Ashraf Kiyani, Tehmina Shehryar, Samina Khalid, Uzma Jamil, Adeel Muzaffar Syed · 2023 · International Journal of Imaging Systems and Technology
  20. Extracting Strategies for Improving Internet-of-Things-Based Home Industries in Iran: A Strengths, Weaknesses, Opportunities, and Threats Analysis
    Reza Mahmoudi, Siyavosh Roozi, Ali Mohammad Saghiri, Ali Mahmoudi · 2020 · IEEE Transactions on Engineering Management
  21. A comprehensive overview on intelligent mechanical systems and its applications
    Shibin David, R.S. Anand, Sarah Sheikh, S. Jebapriya, J. Andrew, S. Basil Xavier · 2020 · Materials Today Proceedings
  22. Relevance of advanced imaging analysis units in radiology departments: a narrative review
    Teodoro Martín‐Noguerol, Félix Paulano‐Godino, Pilar López Úbeda, Roy Riascos, Antonio Luna · 2025 · International Journal of Computer Assisted Radiology and Surgery
  23. The Impacts of Subthalamic Nucleus-Deep Brain Stimulation (STN-DBS) on the Neuropsychiatric Function of Patients with Parkinson’s Disease Using Image Features of Magnetic Resonance Imaging under the Artificial Intelligence Algorithms
    Wei Chen, Maode Wang, Ning Wang, Changwang Du, Xudong Ma, Qi Li · 2021 · Contrast Media & Molecular Imaging
  24. Analyzing the Effectiveness of ML Agents in Enhancing the Predictive Model in Decision Making for Medical Practitioners in the Healthcare Industry: A Structural Equation Model Analysis
    Anand Prakash Dube, Raghav Yadav · 2022 · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
  25. Prediction of Coronary Artery Disease using Artificial Intelligence – A Systematic Literature Review
    G. Ramanathan, S. N. Jagadeesha · 2023 · International Journal of Health Sciences and Pharmacy
  26. Artificial intelligence technology in MR neuroimaging. А radiologist’s perspective
    Г. Е. Труфанов, Aleksandr Yu. Efimtsev · 2023 · Russian Journal for Personalized Medicine
  27. Clinical Significance of Action Research-Based Seamless Care to Improve Imaging Efficiency and Patients’ Cognition, and Alleviate Patient Anxiety
    Haiqin Zhang, Hui Miao, Donglan Yue, Jue Xia · 2023 · International Journal of General Medicine
  28. Natural language processing and LLMs in liver imaging: a practical review of clinical applications
    Pilar López Úbeda, Teodoro Martín‐Noguerol, Antonio Luna · 2025 · Abdominal Radiology
  29. A Survey on Machine Learning Based Medical Assistive Systems in Current Oncological Sciences
    Bhawna Goyal, Bobbinpreet Kaur, Ebenezer Daniel · 2021 · Current Medical Imaging Formerly Current Medical Imaging Reviews
  30. Associations between clinical neck symptoms and various evaluations ofcervical intervertebral disc degeneration by magnetic resonance imaging
    Otaki Haruka, Koji Otani, Takehiro Watanabe, Miho Sekiguchi, Shin‐ichi Konno · 2021 · FUKUSHIMA JOURNAL OF MEDICAL SCIENCE
  31. The Role of Artificial Intelligence in Diagnostic Radiology: Knowledge, Attitude, and Practice of Radiologists and Radiology Residents in Kenya
    Edward Kamau Mwaniki, Callen Kwamboka Onyambu, John Chris Rodrigues · 2023 · Research Square
  32. AI classification of knee prostheses from plain radiographs and real-world applications
    Prin Twinprai, Ong-art Phruetthiphat, Krit Wongwises, Rit Apinyankul, Puripong Suthisopapan, Wongthawat Liawrungrueang, Nattaphon Twinprai · 2025 · European Journal of Orthopaedic Surgery & Traumatology
  33. Enhanced wildfire detection and semantic segmentation via fine-tuned deep learning models
    Nguyễn Hồng Quang, Hanna Lee, Seunghyo Ahn, Gihong Kim · 2025 · Earth Science Informatics
  34. A Framework for Performance Optimization of Internet of Things Applications
    Osama Almurshed, Souham Meshoul, Asmail Muftah, Ashish Kumar Kaushal, Osama Almoghamis, Ioan Petri, Nitin Auluck, OMER F. RANA · 2024 · Lecture notes in computer science
  35. AI is not Always the Enemy: Please, Disambiguate Before You Hate
    Teodoro Martín‐Noguerol, Pilar López Úbeda, Antonio Luna · 2025 · Academic Radiology
  36. Radiologist’s Role in Artificial Intelligence Era
    Sornsupha Limchareon, Sutasinee Kongpromsuk, Podchara Klinwichit, Athitha On-uean · 2022 · Siriraj Medical Journal/San Sirirat
  37. Advancements in Healthcare
    Dwith Chenna · 2024 · Advances in medical diagnosis, treatment, and care (AMDTC) book series
  38. Cross-country patterns in radiography student readiness for artificial intelligence
    Mohamed Zakaria El-Sayed, Mohammad Ahmmad Rawashdeh, A. Moossa, Maryam Atfah, B Prajna, H.G.E.M.A. Hassan, Mohamed G. Khattap, Mahmoud A. A. Bekheet, I Islam, M.G. Haggag et al. · 2025 · Radiography
  39. When the white coat meets the code: medical professionals’ negotiating with artificial intelligence, trust and boundary work
    Laura Sartori, Marianna Musmeci, Sara Cannizzaro, Chiara Binelli · 2026 · Health Risk & Society
  40. Free web tool for comprehensive ROC analysis
    Yury Kirpichev, Yuriy Aleksandrovich Vasilev, Anton V. Vladzymyrskyy, Olga V. Omelyanskaya, Серафим Сергеевич Семенов, Tatiana Bobrovskaya, Kirill M. Arzamasov · 2025 · Biological Communications
  41. Quality and Data Science
    Bibb Allen, Tessa Sundaram Cook, Jacqueline A. Bello · 2019 · Journal of the American College of Radiology
  42. A Basic Primer of Artificial Intelligence for Radiologists
    Ethan Stahl, Steven L. Blumer · 2021 · Contemporary Diagnostic Radiology
  43. Artificial Intelligence in Radiology: A Fast-Food Versus Slow-Food Question?
    Teodoro Martín‐Noguerol, Pilar López Úbeda, Antonio Luna · 2023 · Journal of the American College of Radiology
  44. Beneficios y Riesgos de la Implementación de Inteligencia Artificial en los Procesos de Diagnóstico Médico en el Ecuador
    Katherine Xeomara Galarza Medina, Katherine Maldonado Coronel, Mónica Silvana Herrera Guanopatin · 2024 · Ciencia Latina Revista Científica Multidisciplinar
  45. Artificial Intelligence in Early Detection of Cervical Intraepithelial Neoplasia
    Lalasa Mukku, Jyothi Thomas · 2024 · International Journal of Innovative Science and Research Technology (IJISRT)
  46. Emerging MRI Biomarkers for Prognostication in Rectal Cancer
    Apekshya Singh, Xiaofu Li, Shun-Bing Shi, Han Liu, Yu‐Peng Wu, Sanjeev Nirala · 2024 · Current Cancer Therapy Reviews
  47. Leveraging AI in arts: a case study of music creating venture EnterArts
    Suk-Ki Hong, Hong‐Hee Lee · 2025 · Service Business
  48. Implementation of artificial intelligence in detection, classification, and prognostication of osteosarcoma utilizing different assessment techniques: a systematic review
    Zhina Mohamadi, Paniz Partovifar, Helia Ahmadzadeh, Elmira Ali Ahmadi, Ali Ghanbari, Sina Feyzipour, Fatemeh Atefat, Nazanin Jahanpeyma, Fatemeh Haghighi asl, Armin ZarinKhat et al. · 2025 · Intelligence-Based Medicine
  49. Business Readiness for Implementation of AI Prevention of Potential Risks in Natural Gas Transmission and Storage
    Petya Biolcheva · 2021 · International Journal of Earth & Environmental Sciences
  50. The Classification of the Prostate Cancer based on Transfer Learning Techniques
    Ola S. Khedr, Mohamed El-Sayed Wahed, Al-Sayed R. Al-Attar, E. A. Abdel-Rehim · 2023 · Research Square
  51. “First, Do No Harm” in the Digital Era: Examining the Practicality of the European Health Data Space Proposal and Ethical Implications of Artificial Intelligence. A Systematic Literature Review
    Ana Rita Ferreira, Irina Alho, Ana Luísa Neves, Henrique Lopes, Mónica Maria Bessa Correia · 2025 · SSRN Electronic Journal
  52. WITHDRAWN: Optimizing Clinical Adoption of Large Language Models in Hepatology: Toward Terminological Precision, Multilingual Adaptability, and Interpretive Literacy
    Tong Zhou · 2025 · Journal of Hepatology · Retracted
  53. Computed Tomography for Preoperative Colorectal Staging Prediction Based on Deep Multi-task Learning
    Hualin Yang, Guo Shuxu, Kan He, Jinzhu Yang, Yu Lian Guo, Yunhai Qiu, Huimao Zhang, Xueyan Li · 2020 · International Symposium on Image Computing and Digital Medicine (ISICDM)
  54. How Artificial Intelligence will Reshape the Field of Cardiothoracic Imaging: A Global Perspective
    Carlo Nicola De Cecco, Jie Zhang, Marly van Assen, Jack Wessell, Tim Leiner, Bin Lü · 2022 · Contemporary medical imaging
  55. A Case Study on Coronary Heart Disease using Machine Learning Techniques
    G. Ramanathan, S. N. Jagadeesha · 2022 · International Journal of Health Sciences and Pharmacy
  56. CONSERVATIVE SURVEY OF MACHINE LEARNING AND DATA ANALYTICS
    Oluyinka Iyabo Omotosho · 2023 · IJRDO -Journal of Computer Science Engineering
  57. Enhancing Precision Medicine and Wellness with Computing and AI across Clinical, Imaging, Environmental, Multi-Omics, Wearable Sensors, and Socio-Cognitive Data
    Yves A. Lussier · 2023 · Elsevier eBooks
  58. Reply to the letter to the editor: “A critical evaluation on the use of large language model for radiology research”
    Pilar López Úbeda, Teodoro Martín‐Noguerol, Antonio Luna · 2023 · European Radiology
  59. Machine learning
    Mohammad Ali Ahmadi · 2024 · Elsevier eBooks
  60. A Review of Machine Learning for Additive Manufacturing
    Beyza Gavcar · 2024 · Lecture notes in networks and systems
  61. Role of radiologist with the advent of artificial intelligence in medical imaging
    Anitha Boregowdanapalya · 2024 · International Journal of Research in Medical Sciences
  62. Natural language processing evaluation of trends in cervical cancer incidence in radiology reports: A ten-year survey
    Pilar López Úbeda, Teodoro Martín‐Noguerol, Antonio Luna · 2025 · Radiography
  63. Enhancing Panic Attack Predictions: Addressing Data Imbalance in Machine Learning Models
    Fazrul Ridha Alliandre, Erna Hikmawati · 2025 · International Conference on Software and Computer Applications (ICSCA)
  64. From Task-Specific Models to Generative AI: Rethinking Radiology’s Technological Roadmap
    Pilar López Úbeda, Teodoro Martín‐Noguerol, Antonio Luna · 2025 · Academic Radiology
  65. Perspectives of nuclear medicine professionals on artificial intelligence and educational implications
    Hongyan Yin, Dai Shi, Can Meng · 2025 · Discover Artificial Intelligence
  66. Additional file 2 of Deep learning–based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features
    Yang, Liping, Wang, Tianzuo, Zhang, Jinling, Kang, Shi, Shichuan Xu, Wang, Kezheng · 2024 · Figshare
  67. Additional file 1 of Robot-assisted surgery and artificial intelligence-based tumour diagnostics: social preferences with a representative cross-sectional survey
    Áron Hölgyesi, Zsombor Zrubka, Gulácsi, László, Petra Baji, Tamás P. Haidegger, Kozlovszky, Miklós, Miklós Weszl, Kovács, Levente, Márta Péntek · 2024 · Figshare
  68. Additional file 2 of Robot-assisted surgery and artificial intelligence-based tumour diagnostics: social preferences with a representative cross-sectional survey
    Áron Hölgyesi, Zsombor Zrubka, Gulácsi, László, Petra Baji, Tamás P. Haidegger, Kozlovszky, Miklós, Miklós Weszl, Kovács, Levente, Márta Péntek · 2024 · Figshare
  69. Additional file 3 of Robot-assisted surgery and artificial intelligence-based tumour diagnostics: social preferences with a representative cross-sectional survey
    Áron Hölgyesi, Zsombor Zrubka, Gulácsi, László, Petra Baji, Tamás P. Haidegger, Kozlovszky, Miklós, Miklós Weszl, Kovács, Levente, Márta Péntek · 2024 · Figshare
  70. Additional file 1 of Deep learning–based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features
    Yang, Liping, Wang, Tianzuo, Zhang, Jinling, Kang, Shi, Shichuan Xu, Wang, Kezheng · 2024 · Figshare
  71. Preparing radiology programs for the oral boards: A checklist for success informed by SWOT analysis
    Brandon J. Ritchie, Kaustav Bera, Max Sheng, Inas Mohamed, Nikhil Ramaiya · 2026 · Current Problems in Diagnostic Radiology
  72. High Accuracy but Low Explainability: The Challenge of Explainable Artificial Intelligence in Multiple Sclerosis Assessment From Magnetic Resonance Imaging Radiology Reports
    Teodoro Martín‐Noguerol, Pilar López Úbeda, Jorge Escartin, Suyash Mohan, Antonio Luna · 2026 · Seminars in Ultrasound CT and MRI
  73. Rethinking “Useful” and “Useless” AI in radiology
    Teodoro Martín‐Noguerol, Pilar López Úbeda, Antonio Luna · 2026 · Current Problems in Diagnostic Radiology
  74. Implications de l’intelligence artificielle au travail et adaptation des individus : l’apport du job crafting
    Fabienne Perez · 2021 · theses.fr (ABES)
  75. Interfacial charge transfer dynamics between MA0.5Cs0.5PbBr3 and 8-aminoquinoline and the application of AI–ML-based soft computing to predict photoluminescence quantum yield
    Sourav Mandal, Suraj Barman, Sourav Nandi, Subhadip Giri, Arijit Maity, Anwesha Misra, Ajay Misra · 2026 · Journal of Photochemistry and Photobiology A Chemistry