Cardiothoracic anaesthesia in the digital age: The application of artificial intelligence

Abstract

Author(s): Dilip Vijay, Sanjay Ashwamedh Kshirsagar, Amit Anand, Sheetal Panwar*, Sandeep Manne, Akshaya N Shetti

In the ever-evolving landscape of medical technology, the integration of artificial intelligence (AI) has emerged as a transformative force in various specialties, including anaesthesia. Cardiothoracic anaesthesia, a critical domain within cardiovascular medicine, stands to benefit significantly from AI's capabilities. This abstract delves into the burgeoning intersection of cardiothoracic anaesthesia and AI, exploring the manifold applications, challenges, and potential outcomes. AI's capacity to analyze complex data streams swiftly and accurately has paved the way for personalized patient care in the digital age. In the context of cardiothoracic anaesthesia, AI's potential spans preoperative risk assessment, intraoperative monitoring, and postoperative care optimization. Algorithms trained on extensive patient datasets can predict patient-specific responses to anaesthesia, aiding clinicians in tailoring interventions. Furthermore, real-time AI-driven monitoring systems can detect subtle changes in hemodynamic and oxygenation, enabling timely intervention and improving patient safety during surgery. However, this symbiotic relationship between AI and cardiothoracic anaesthesia faces challenges, including data privacy concerns, algorithm interpretability, and integration with existing healthcare systems. Ensuring that AI models are trained on diverse and representative datasets is essential to mitigate biases and promote equitable patient care

Share this article

Awards Nomination

Editors List

  • Prof. Elhadi Miskeen

    Obstetrics and Gynaecology Faculty of Medicine, University of Bisha, Saudi Arabia

  • Ahmed Hussien Alshewered

    University of Basrah College of Medicine, Iraq

  • Sudhakar Tummala

    Department of Electronics and Communication Engineering SRM University – AP, Andhra Pradesh

     

     

     

  • Alphonse Laya

    Supervisor of Biochemistry Lab and PhD. students of Faculty of Science, Department of Chemistry and Department of Chemis

     

  • Fava Maria Giovanna

     

Google Scholar citation report
Citations : 170

Onkologia i Radioterapia received 170 citations as per Google Scholar report

Onkologia i Radioterapia peer review process verified at publons
Indexed In
  • Directory of Open Access Journals
  • Scimago
  • SCOPUS
  • EBSCO A-Z
  • MIAR
  • Euro Pub
  • Google Scholar
  • Medical Project Poland
  • PUBMED
  • Cancer Index
  • Gdansk University of Technology, Ministry Points 20