Рақамли технологияларнинг назарий ва амалий масалалари 7-том 1-сан (2024) · 16-23-беттер

Do Medicines Need GPT-4: Analysis of Current World Experience

Адылова, Ф.Т., Давронов, Р.Р.

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Аннотация

Large Language Models (LLM) have demonstrated remarkable capabilities in understanding and generating natural language in various fields, including medicine. The article presents an assessment of GMT-4 based on two points of view on the problem of applying this language model: developers from Open AI, Microsoft and medical users from two European projects. Over the past few years, LLMs trained on massive interdisciplinary corpuses have become powerful blocks in building task-oriented systems. The article considers three tasks: medical education, the efficiency of ChatGPT-4 in the clinic (consultations, transcripts of the conversation between the doctor and the patient ), and specific levels of diagnostic accuracy (different fields of medicine). The answer to the question about the need for medical GPT is in the world - it is positive.

LLMOpenAIGPT-4ChatGPT-4LLMOpenAIGPT-4ChatGPT-4

Метадайындар булагы: журналдын OAI-PMH архиви · Sindex толук текстти сактабайт, булакка шилтеме берет.

Цитата алуу

APA 7
Адылова, Ф.Т. & Давронов, Р.Р. (2024). Do Medicines Need GPT-4: Analysis of Current World Experience. Рақамли технологияларнинг назарий ва амалий масалалари, 7(1), 16-23.
GOST R 7.0.5
Адылова, Ф.Т., Давронов, Р.Р. Do Medicines Need GPT-4: Analysis of Current World Experience // Рақамли технологияларнинг назарий ва амалий масалалари. 2024. Т. 7. № 1. С. 16-23.
BibTeX
@article{ф.т.2024,
  author  = {Адылова, Ф.Т. and Давронов, Р.Р.},
  title   = {Do Medicines Need GPT-4: Analysis of Current World Experience},
  journal = {Рақамли технологияларнинг назарий ва амалий масалалари},
  year    = {2024},
  volume  = {7},
  number  = {1},
  pages   = {16-23}
}
RIS
TY  - JOUR
AU  - Адылова, Ф.Т.
AU  - Давронов, Р.Р.
TI  - Do Medicines Need GPT-4: Analysis of Current World Experience
JO  - Рақамли технологияларнинг назарий ва амалий масалалари
PY  - 2024
VL  - 7
IS  - 1
SP  - 16
EP  - 23
ER  -