Large language Models in Medicine

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This investigation looked to lead a settable survey of the existing literature selecting cloud computing by ventures. This included recognizing the ebb and flow commitments of IS inquire about with respect to the marvel and deciding the under-examined issues and the commitments of IS explore in regards to the wonder. The articles was arrange, into articles, discoveries and future suggest for future IS re-seek roads are as per speculations, examine techniques, and cloud computing reception factors and procedures that were recognized by utilizing GT approach.1. The main aim of the study was to identify the use of cloud computing in relations to current methodologies, theoretical framework, challenges, publication years, by the researchers who's study were reviewed.2. The findings of the review revealed that most of researchers used the TAM and DOI models as the standard models for their studies3. Most of the research as found in the review made use of the survey as well as case study methods. 4. The key analysis units focus on acceptance and adoption of the use of cloud computing.

Autorentext

Abdulkader Helwan - postdok w Uniwersitete Linchepinga, na fakul'tete zdrawoohraneniq, mediciny i nauk o zabote (HMV). Poluchil stepeni magistra i doktora filosofii w oblasti biomedicinskoj inzhenerii w Blizhnewostochnom uniwersitete na Kipre, gde prowodil rqd issledowanij w oblasti mashinnogo obucheniq i biomediciny w centre prikladnogo iskusstwennogo intellekta.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786207455355
    • Genre Business Administration
    • Sprache Englisch
    • Anzahl Seiten 64
    • Herausgeber LAP LAMBERT Academic Publishing
    • Größe H220mm x B150mm x T4mm
    • Jahr 2023
    • EAN 9786207455355
    • Format Kartonierter Einband
    • ISBN 6207455355
    • Veröffentlichung 29.12.2023
    • Titel Large language Models in Medicine
    • Autor Mohammad K. S Ma'aitah , Abdulkader Helwan
    • Untertitel Applications of LLMs in Medical Imaging and Medical Language Processing
    • Gewicht 113g

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