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Number №3, 2024

Telemedicine today: trends in the use of telemedicine consultations based on regional experience

Number №2, 2024

Mobile apps for psychological well-being: user attitudes and definition of requirements

Number №1, 2024

Diagnosis in the era of digital medicine

Number №4, 2023

Artificial intelligence in Russian healthcare: collecting and preparing data for machine learning

Number №3, 2023

China as a supplier of medical equipment in the Russian Federation. Options for cooperation and features of working with Chinese suppliers

Number №2, 2023

Experience in teaching telemedicine in the system of higher professional education The attitude of medical workers to telemedicine technologies

Number №4, 2022

Physician burnout: the hidden healthcare crisis. Results of an online survey of doctors

Number №3, 2022

Interaction of clinical and diagnostic medicine. Results of an online survey of doctors

Number №2, 2022

Mobile applications for mental health self-management: a review of customers’ opinions Ultrasound robots: ready-to-use solutions and perspective directions

Number №1, 2022

Digital transformation of the pathological service as a way to improve the quality of medical care

Number №4, 2021

Clinical guidelines of the Ministry of Health of the Russian Federation: are doctors ready to follow them? Results of an online survey of doctors.

Number №3, 2021

Виртуальная реальность (VR) в клинической медицине: международный и российский опыт

Number №2, 2021

Дистанционные консультации пациентов: что изменилось за 20 лет?

Number №1, 2021

Experience of participation in the blood pressure telemonitoring pilot project of the Ministry of Healthcare

Number №4, 2020

Автоматизация процесса выявления у беременных заболевания COVID-19

Number №3, 2020

Remote cognitive behavioral therapy for stress disorder associated with the COVID-19 pandemic

Number №2, 2020

Distance education at a medical school during the COVID-19 pandemic: the first experience through the eyes of students

Number №1-2, 2018

Ответственность при использовании телемедицины: врач или юрист
Скрининг меланомы: искусственный интеллект, mHealth и теледерматология

Number №3, 2018 год

II Всероссийский форум по телемедицине, цифровизации здравоохранения и медицинскому маркетингу «ТЕЛЕМЕДФОРУМ 2019»
Эффективность телемедицинских консультаций «пациент-врач»
Телереабилитация: рандомизированное исследование исходов

Number №1-2, 2019

Роль искусственного интеллекта в медицине
Информационная система поддержки принятия врачебных решений

Number №1, 2020

Technologies for continuous monitoring of blood pressure: prospects for practical application
Telemedicine technologies in the Chinese army

Number №2, 2017

Primary telemedicine consultation "patient-doctor": first systematization of methodology

Number №1, 2017

1. A systematic review of using Internet messengers in telemedicine
2. Telemedicine and social networks in the fight against drug addiction

Number №1, 2016

1. The Experience of the Telehealth Network of Minas Gerais, Brazil
2. The Remote Monitoring of Patients with Congestive Heart Failure:The Organizational
Impact..

Number №1, 2015

Teleassessment for diagnosis and treatment in urology
Efficiency of telemedicine at the northern regions Russian Federation A.L. Tsaregorodtsev

Abstract in Russian /

Article in Russian

Number №1, 2024 - page 33-43

ChatGPT in medicine: opportunities and limitations DOI: 10.29188/2712-9217-2024-10-1-33-43

For citation: Shaderkina V.A. ChatGPT in medicine: opportunities and limitations. Russian Journal of Telemedicine and E-Health 2024;10(1):33-43; https://doi.org/10.29188/2712-9217-2024-10-1-33-43

Shaderkina V.A.

Shaderkina V.A. – Scientific editor of the urological information portal UroWeb.ru; RSCI Author ID 880571, https://orcid.org/0000-0002-8940-4129

300

Introduction. ChatGPT and similar large language model (LLM)/artificial intelligence (AI)-based technologies have been actively implemented in medicine worldwide over the past few years.

Materials and Methods. The author analysed the available literature on the application of large language models (LLM, BNM, AI) in medicine and gave his opinion on whether AI/ChatGPT can replace the physician and whether ChatGPT integration into medicine is to be feared.

Results. The place of AI/ChatGPT in medicine is yet to be determined, but we can already identify areas of its use – evaluation of medical data and support for clinical decisions, training and professional development of medical professionals, management and processing of large amounts of documentation, support for communication with patients, including highly personalised communication with patients and their relatives.

However, it should be taken into account that ChatGPT/ AI is an evolving tool that is currently difficult to call perfect. Despite its high level of development, AI/ChatGPT can make mistakes, especially if it has been trained on incomplete, insufficient or biased data. For example, the AI may not take into account social, psychological, and economic factors of patients, which are critical for proper diagnosis and treatment. Moreover, a known factor is AI/ChatGPT «hallucinations», a format that generates incorrect, fictitious data («hallucinations»), requiring additional verification of information by medical personnel. Separate issues that remain unresolved are patient data privacy and legal and ethical responsibilities.

Conclusions. The prospects for the application of LLM/ AI/ChatGPT in medicine are limitless and include improved medical efficiency and patient interaction, decision support and administrative assistance, potential for educational and research applications, and democratisation of AI technologies. Regardless of our attitude towards ChatGPT, the development of AI is unstoppable. The most prudent course of action is to embrace it and harness its potential to improve human health care. The development of measures to ensure data security and ethical use of LLM/ AI/ChatGPT is required.