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  1. Article: The Emergence Phenomenon in Artificial Intelligence: A Warning Sign on the Path to Artificial General Intelligence.

    Sorin, Vera / Klang, Eyal

    The Israel Medical Association journal : IMAJ

    2024  Volume 26, Issue 2, Page(s) 120–121

    MeSH term(s) Humans ; Artificial Intelligence ; Intelligence
    Language English
    Publishing date 2024-02-29
    Publishing country Israel
    Document type Journal Article
    ZDB-ID 2008291-5
    ISSN 1565-1088 ; 0021-2180
    ISSN 1565-1088 ; 0021-2180
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5470: Show issues Location:
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  2. Article ; Online: Can advanced technologies help address the global increase in demand for specialized medical care and improve telehealth services?

    Lahat, Adi / Klang, Eyal

    Journal of telemedicine and telecare

    2023  , Page(s) 1357633X231155520

    Language English
    Publishing date 2023-02-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 1340281-x
    ISSN 1758-1109 ; 1357-633X
    ISSN (online) 1758-1109
    ISSN 1357-633X
    DOI 10.1177/1357633X231155520
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  3. Article ; Online: Evaluation of OpenAI's large language model as a new tool for writing papers in the field of thrombosis and hemostasis.

    Klang, Eyal / Levy-Mendelovich, Sarina

    Journal of thrombosis and haemostasis : JTH

    2023  Volume 21, Issue 4, Page(s) 1055–1058

    MeSH term(s) Humans ; Hemostasis ; Language ; Thrombosis ; Writing
    Language English
    Publishing date 2023-01-20
    Publishing country England
    Document type Letter
    ZDB-ID 2112661-6
    ISSN 1538-7836 ; 1538-7933
    ISSN (online) 1538-7836
    ISSN 1538-7933
    DOI 10.1016/j.jtha.2023.01.011
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  4. Article ; Online: Revolutionizing patient safety with artificial intelligence: the potential of natural language processing and large language models.

    Klang, Eyal / García-Elorrio, Ezequiel / Zimlichman, Eyal

    International journal for quality in health care : journal of the International Society for Quality in Health Care

    2023  Volume 35, Issue 3

    MeSH term(s) Humans ; Artificial Intelligence ; Natural Language Processing ; Patient Safety ; Language
    Language English
    Publishing date 2023-07-08
    Publishing country England
    Document type Journal Article
    ZDB-ID 1194150-9
    ISSN 1464-3677 ; 1353-4505
    ISSN (online) 1464-3677
    ISSN 1353-4505
    DOI 10.1093/intqhc/mzad049
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    Zs.A 3052: Show issues Location:
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  5. Article: Large language models and the emergence phenomena.

    Sorin, Vera / Klang, Eyal

    European journal of radiology open

    2023  Volume 10, Page(s) 100494

    Abstract: This perspective explores the potential of emergence phenomena in large language models (LLMs) to transform data management and analysis in radiology. We provide a concise explanation of LLMs, define the concept of emergence in machine learning, offer ... ...

    Abstract This perspective explores the potential of emergence phenomena in large language models (LLMs) to transform data management and analysis in radiology. We provide a concise explanation of LLMs, define the concept of emergence in machine learning, offer examples of potential applications within the radiology field, and discuss risks and limitations. Our goal is to encourage radiologists to recognize and prepare for the impact this technology may have on radiology and medicine in the near future.
    Language English
    Publishing date 2023-06-06
    Publishing country England
    Document type Journal Article
    ZDB-ID 2810314-2
    ISSN 2352-0477
    ISSN 2352-0477
    DOI 10.1016/j.ejro.2023.100494
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  6. Article: US supreme court decision: the gastroenterological perspective.

    Lahat, Adi / Klang, Eyal

    Therapeutic advances in gastroenterology

    2022  Volume 15, Page(s) 17562848221116935

    Language English
    Publishing date 2022-08-22
    Publishing country England
    Document type Journal Article
    ZDB-ID 2440710-0
    ISSN 1756-2848 ; 1756-283X
    ISSN (online) 1756-2848
    ISSN 1756-283X
    DOI 10.1177/17562848221116935
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  7. Article ; Online: Bidirectional Encoder Representations from Transformers in Radiology: A Systematic Review of Natural Language Processing Applications.

    Gorenstein, Larisa / Konen, Eli / Green, Michael / Klang, Eyal

    Journal of the American College of Radiology : JACR

    2024  

    Abstract: Introduction: Bidirectional Encoder Representations from Transformers (BERT), introduced in 2018, has revolutionized natural language processing. Its bidirectional understanding of word context has enabled innovative applications, notably in radiology. ... ...

    Abstract Introduction: Bidirectional Encoder Representations from Transformers (BERT), introduced in 2018, has revolutionized natural language processing. Its bidirectional understanding of word context has enabled innovative applications, notably in radiology. This study aimed to assess BERT's influence and applications within the radiologic domain.
    Methods: Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a systematic review, searching PubMed for literature on BERT-based models and natural language processing in radiology from January 1, 2018, to February 12, 2023. The search encompassed keywords related to generative models, transformer architecture, and various imaging techniques.
    Results: Of 597 results, 30 met our inclusion criteria. The remaining were unrelated to radiology or did not use BERT-based models. The included studies were retrospective, with 14 published in 2022. The primary focus was on classification and information extraction from radiology reports, with x-rays as the prevalent imaging modality. Specific investigations included automatic CT protocol assignment and deep learning applications in chest x-ray interpretation.
    Conclusion: This review underscores the primary application of BERT in radiology for report classification. It also reveals emerging BERT applications for protocol assignment and report generation. As BERT technology advances, we foresee further innovative applications. Its implementation in radiology holds potential for enhancing diagnostic precision, expediting report generation, and optimizing patient care.
    Language English
    Publishing date 2024-01-30
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2274861-1
    ISSN 1558-349X ; 1546-1440
    ISSN (online) 1558-349X
    ISSN 1546-1440
    DOI 10.1016/j.jacr.2024.01.012
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    Zs.A 6636: Show issues Location:
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  8. Article ; Online: Utilizing Natural Language Processing and Large Language Models in the Diagnosis and Prediction of Infectious Diseases: A Systematic Review.

    Omar, Mahmud / Brin, Dana / Glicksberg, Benjamin / Klang, Eyal

    American journal of infection control

    2024  

    Abstract: Background: Natural Language Processing (NLP) and Large Language Models (LLMs) hold largely untapped potential in infectious disease management. This review explores their current use and uncovers areas needing more attention.: Methods: This analysis ...

    Abstract Background: Natural Language Processing (NLP) and Large Language Models (LLMs) hold largely untapped potential in infectious disease management. This review explores their current use and uncovers areas needing more attention.
    Methods: This analysis followed systematic review procedures, registered with PROSPERO. We conducted a search across major databases including PubMed, Embase, Web of Science, and Scopus, up to December 2023, using keywords related to NLP, LLM, and infectious diseases. We also employed the QUADAS-2 tool for evaluating the quality and robustness of the included studies.
    Results: Our review identified 15 studies with diverse applications of NLP in infectious disease management. Notable examples include GPT-4's application in detecting urinary tract infections and BERTweet's use in Lyme Disease surveillance through social media analysis. These models demonstrated effective disease monitoring and public health tracking capabilities. However, the effectiveness varied across studies. For instance, while some NLP tools showed high accuracy in pneumonia detection and high sensitivity in identifying invasive mold diseases from medical reports, others fell short in areas like bloodstream infection management.
    Conclusion: This review highlights the yet-to-be-fully-realized promise of NLP and LLMs in infectious disease management. It calls for more exploration to fully harness AI's capabilities, particularly in the areas of diagnosis, surveillance, predicting disease courses, and tracking epidemiological trends.
    Language English
    Publishing date 2024-04-06
    Publishing country United States
    Document type Journal Article
    ZDB-ID 392362-9
    ISSN 1527-3296 ; 0196-6553
    ISSN (online) 1527-3296
    ISSN 0196-6553
    DOI 10.1016/j.ajic.2024.03.016
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1773: Show issues Location:
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  9. Article ; Online: Large language models and the emergence phenomena

    Vera Sorin / Eyal Klang

    European Journal of Radiology Open, Vol 10, Iss , Pp 100494- (2023)

    2023  

    Abstract: This perspective explores the potential of emergence phenomena in large language models (LLMs) to transform data management and analysis in radiology. We provide a concise explanation of LLMs, define the concept of emergence in machine learning, offer ... ...

    Abstract This perspective explores the potential of emergence phenomena in large language models (LLMs) to transform data management and analysis in radiology. We provide a concise explanation of LLMs, define the concept of emergence in machine learning, offer examples of potential applications within the radiology field, and discuss risks and limitations. Our goal is to encourage radiologists to recognize and prepare for the impact this technology may have on radiology and medicine in the near future.
    Keywords LLMs ; ChatGPT ; Emergence ; Generative models ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: Gallbladder Metastasis from a Gastric Origin.

    Gorenstein, Larisa / Soffer, Shelly / Klang, Eyal

    The Israel Medical Association journal : IMAJ

    2023  Volume 25, Issue 5, Page(s) 372–373

    MeSH term(s) Humans ; Gallbladder Neoplasms/diagnosis ; Gallbladder Neoplasms/secondary ; Stomach ; Abdomen
    Language English
    Publishing date 2023-05-26
    Publishing country Israel
    Document type Journal Article
    ZDB-ID 2008291-5
    ISSN 1565-1088 ; 0021-2180
    ISSN 1565-1088 ; 0021-2180
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