These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

579 related articles for article (PubMed ID: 31745604)

  • 1. [Radiomics-AI-based image analysis].
    Demircioğlu A
    Pathologe; 2019 Dec; 40(Suppl 3):271-276. PubMed ID: 31745604
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Demystification of AI-driven medical image interpretation: past, present and future.
    Savadjiev P; Chong J; Dohan A; Vakalopoulou M; Reinhold C; Paragios N; Gallix B
    Eur Radiol; 2019 Mar; 29(3):1616-1624. PubMed ID: 30105410
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Artificial Intelligence Solutions for Analysis of X-ray Images.
    Adams SJ; Henderson RDE; Yi X; Babyn P
    Can Assoc Radiol J; 2021 Feb; 72(1):60-72. PubMed ID: 32757950
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.
    Tran WT; Sadeghi-Naini A; Lu FI; Gandhi S; Meti N; Brackstone M; Rakovitch E; Curpen B
    Can Assoc Radiol J; 2021 Feb; 72(1):98-108. PubMed ID: 32865001
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists.
    Pesapane F; Tantrige P; Patella F; Biondetti P; Nicosia L; Ianniello A; Rossi UG; Carrafiello G; Ierardi AM
    Med Oncol; 2020 Apr; 37(5):40. PubMed ID: 32246300
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.
    Thrall JH; Li X; Li Q; Cruz C; Do S; Dreyer K; Brink J
    J Am Coll Radiol; 2018 Mar; 15(3 Pt B):504-508. PubMed ID: 29402533
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology.
    Martín Noguerol T; Paulano-Godino F; Martín-Valdivia MT; Menias CO; Luna A
    J Am Coll Radiol; 2019 Sep; 16(9 Pt B):1239-1247. PubMed ID: 31492401
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Adapting to Artificial Intelligence: Radiologists and Pathologists as Information Specialists.
    Jha S; Topol EJ
    JAMA; 2016 Dec; 316(22):2353-2354. PubMed ID: 27898975
    [No Abstract]   [Full Text] [Related]  

  • 9. Workflow Applications of Artificial Intelligence in Radiology and an Overview of Available Tools.
    Kapoor N; Lacson R; Khorasani R
    J Am Coll Radiol; 2020 Nov; 17(11):1363-1370. PubMed ID: 33153540
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning in Medical Imaging.
    Giger ML
    J Am Coll Radiol; 2018 Mar; 15(3 Pt B):512-520. PubMed ID: 29398494
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology.
    Tang A; Tam R; Cadrin-Chênevert A; Guest W; Chong J; Barfett J; Chepelev L; Cairns R; Mitchell JR; Cicero MD; Poudrette MG; Jaremko JL; Reinhold C; Gallix B; Gray B; Geis R;
    Can Assoc Radiol J; 2018 May; 69(2):120-135. PubMed ID: 29655580
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Artificial intelligence (AI) in radiology? : Do we need as many radiologists in the future?].
    Bonekamp D; Schlemmer HP
    Urologe A; 2022 Apr; 61(4):392-399. PubMed ID: 35277758
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Technical and clinical overview of deep learning in radiology.
    Ueda D; Shimazaki A; Miki Y
    Jpn J Radiol; 2019 Jan; 37(1):15-33. PubMed ID: 30506448
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prime Time for Artificial Intelligence in Interventional Radiology.
    Seah J; Boeken T; Sapoval M; Goh GS
    Cardiovasc Intervent Radiol; 2022 Mar; 45(3):283-289. PubMed ID: 35031822
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [Radiological evaluation of advanced gastric cancer: from image to big data radiomics].
    Tang L
    Zhonghua Wei Chang Wai Ke Za Zhi; 2018 Oct; 21(10):1106-1112. PubMed ID: 30370508
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A narrative review on current imaging applications of artificial intelligence and radiomics in oncology: focus on the three most common cancers.
    Vicini S; Bortolotto C; Rengo M; Ballerini D; Bellini D; Carbone I; Preda L; Laghi A; Coppola F; Faggioni L
    Radiol Med; 2022 Aug; 127(8):819-836. PubMed ID: 35771379
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Artificial intelligence and deep learning - Radiology's next frontier?
    Mayo RC; Leung J
    Clin Imaging; 2018; 49():87-88. PubMed ID: 29161580
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Review of Artificial Intelligence Training Tools and Courses for Radiologists.
    Richardson ML; Adams SJ; Agarwal A; Auffermann WF; Bhattacharya AK; Consul N; Fotos JS; Kelahan LC; Lin C; Lo HS; Nguyen XV; Salkowski LR; Sin JM; Thomas RC; Wassef S; Ikuta I
    Acad Radiol; 2021 Sep; 28(9):1238-1252. PubMed ID: 33714667
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The augmented radiologist: artificial intelligence in the practice of radiology.
    Sorantin E; Grasser MG; Hemmelmayr A; Tschauner S; Hrzic F; Weiss V; Lacekova J; Holzinger A
    Pediatr Radiol; 2022 Oct; 52(11):2074-2086. PubMed ID: 34664088
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Artificial Intelligence and Radiology: Collaboration Is Key.
    Yi PH; Hui FK; Ting DSW
    J Am Coll Radiol; 2018 May; 15(5):781-783. PubMed ID: 29398492
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 29.