Uses of AI in Field of Radiology- What is State of Doctor & Patients Communication in Different Disease for Diagnosis Purpose

Roshan Kumar; Anamika; Ravindra Kumar Nirala; Rajkumar Pradip Ade; Amle Vandana Sonaji

doi:10.55544/jrasb.2.5.9

Authors

Roshan Kumar Assistant Professor, Department of Pharmacy, Shree Dev Bhoomi Institute of Education Science and Technology (SDBIT), Dehradun, INDIA.
Anamika Assistant Professor, Department of Pharmacy, Shree Dev Bhoomi Institute of Education Science and Technology (SDBIT), Dehradun, INDIA.
Ravindra Kumar Nirala Research Scholar, Department of Paramedical (BMRIT), Shree Dev Bhoomi Institute of Education Science and Technology (SDBIT), Dehradun, INDIA.
Rajkumar Pradip Ade Shri Bhairavnath Nisarg Mandal’s Diploma in Pharmacy Institute, Hingoli, Maharashtra, INDIA.
Amle Vandana Sonaji Shri Bhairavnath Nisarg Mandal’s Diploma in Pharmacy Institute, Hingoli, Maharashtra, INDIA.

DOI:

https://doi.org/10.55544/jrasb.2.5.9

Keywords:

AI, Radiology, Doctors-patients Communication, Disease diagnosis

Abstract

Over the course of the past ten years, there has been a rising interest in the application of AI in radiology with the goal of improving diagnostic practises. Every stage of the imaging workflow might potentially be improved by AI, beginning with the ordering of diagnostic procedures and ending with the distribution of data. One of the disadvantages of utilising AI in radiology is that it can disrupt the doctor-patient contact that takes place during the diagnostic procedure. This research synthesis examines how patients and clinicians engage with AI in the process of diagnosing cancer, brain disorders, gastrointestinal tract, and bone-related diseases. [S]ome of the diseases that are studied include cancer, brain disorders, and gastrointestinal tract. Researchers began their investigation of several databases in 2021 and continued their work until 2023. Some of the databases that were examined include PubMed, Embase, Medline, Scopus, and PsycNet. The search terms "artificial intelligence" and "intelligence machine" as well as "communication," "radiology," and "oncology diagnosis" were utilised. It has been demonstrated that artificial intelligence can help medical professionals make more accurate diagnoses. Medical compliance can be enhanced with good training in doctor-patient diagnosis communication, and future research may assist boost patients' trust by informing them of the benefits of AI. Both of these things are important for the delivery of quality medical care.

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