Match tier Listed
Presence Current · Arkansas
Last published 2025
Sources OpenAlex · ORCID
Refreshed 2026-08-08

Anas Alshwayat

Researcher

Also affiliated: King Hussein Cancer Center (2018)

Unknown Researcher

2 h-index 4 pubs 46 cited

  • Machine Learning
  • Carcinoma, Renal Cell
  • Kidney Neoplasms
  • Aged
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Survival Rate
  • SEER Program
  • Internet

Biography and Research Information

OverviewAI-generated summary

Anas Alshwayat's research focuses on the application of machine learning to predict patient outcomes, particularly in the context of cancer. His recent work includes the development of a machine learning-based web tool for personalized survival predictions in chromophobe renal cell carcinoma. Alshwayat also investigates broader medical topics, such as the therapeutic applications of semaglutide and strategies for managing hyponatremia. His scholarship metrics include an h-index of 2 with 4 total publications and 40 citations. He has collaborated with researchers at the University of Arkansas for Medical Sciences, including Nithin Karakala, Anas Radi Issa Alshwayat, Lean Alkhatib, and Krishna Vani Nemalidinne, on shared publications.

Metrics

  • h-index: 2
  • Publications: 4
  • Citations: 46

Selected Publications

  • Calculated Preemptive Strike: Solving Overcorrection of Hyponatremia with Math and Medicine (2025)
    Journal of the American Society of Nephrology DOI OpenAlex
  • The multifaceted effects of semaglutide: exploring its broad therapeutic applications (2025)
    Future Science OA 6 citations DOI OpenAlex
  • Personalized survival predictions in chromophobe renal cell carcinoma: development of a machine learning-based web tool (2025)
    International Urology and Nephrology 1 citation DOI OpenAlex
  • Urine Chemistry: A Valuable Link Binding Kidney Physiology to Patient Care (2024)
    Journal of the American Society of Nephrology DOI OpenAlex
  • Stepwise Teamwork Approach Saves Patients Extensive Work-Up (2024)
    Journal of the American Society of Nephrology DOI OpenAlex

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Collaboration Network

23 Collaborators 12 Institutions 5 Countries

Top Collaborators

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