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Currently submitted to: JMIR Preprints

Date Submitted: Mar 21, 2020

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Artificial intelligence in modern medicine- evolving necessity of the present and role in transforming the future of medical care

  • Pradnya Brijmohan Bhattad; 
  • Vinay Jain

ABSTRACT

The dexterity of computer systems to resemble and mimic human intelligence is artificial intelligence. Artificial intelligence has reformed the diagnostic and therapeutic precision and competence in various fields of medicine. Artificial intelligence appears to play a bright role in the medical diagnosis. Computer systems using artificial intelligence help in assessment of medical images and enormous data. This research aims to identify how the artificial intelligence-based technology is reforming the art of medicine. Artificial intelligence empowers providers in improving efficiency and overall healthcare. Newer machine learning techniques lead the automatic diagnostic systems. Areas of medicine such as medical imaging, automated clinical decision-making support have made significant advances with respect to artificial intelligence technology. With improved diagnosis and prognosis, artificial intelligence possesses the capability to revolutionize various fields of medicine. Artificial intelligence has its own limitations and cannot replace a bedside clinician. In the evolving modern medical digital world, physicians need to support artificial intelligence rather than fear it replacing trained physicians for improved healthcare.


 Citation

Please cite as:

Bhattad PB, Jain V

Artificial intelligence in modern medicine- evolving necessity of the present and role in transforming the future of medical care

JMIR Preprints. 21/03/2020:18829

DOI: 10.2196/preprints.18829

URL: https://preprints.jmir.org/preprint/18829

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