"AI in Medical Writing: A Comparative Analysis of Global and Indian Tools"

Artificial intelligence (AI) is increasingly being utilized in medical writing for literature searches, evidence synthesis, draft creation, summary, language editing, reference analyses, and manuscript preparations. Evidence on the relative performance, reliability, and maturity of different tools is often fragmented. This review aimed to present a function-based comparison of selected global and Indian or India-focused tools relevant to the medical-writing process. The applications, underlying technologies, benefits, limitations, evidence maturity, and contextuality in the Indian setting were described. The technologies include natural language processing, machine learning, generative artificial intelligence, large language models, retrieval-augmented generation, and AI-assisted evidence analysis tools. While the use of AI can enhance efficiency and reduce some burdensome processes, hallucination, fake references, biases, poor reproducibility, privacy concerns, limited contextual understanding, and lack of transparency hinder autonomous use. The novelty of this review includes the provision of a Global–Indian perspective. Thus, AI needs to be considered an assistant requiring human intervention, scientific and ethical safeguards, and further research to develop standardized tool-specific frameworks for evaluations.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-05
DOI
https://doi.org/10.5281/zenodo.23975412
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

"AI in Medical Writing: A Comparative Analysis of Global and Indian Tools"

Chavan Nikita, Pranav Kulkarni, Pranjal Deore, Ambardekar Saumitra
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

"AI in Medical Writing: A Comparative Analysis of Global and Indian Tools"

Chavan Nikita, Pranav Kulkarni, Pranjal Deore, Ambardekar Saumitra
article en

Abstract

Artificial intelligence (AI) is increasingly being utilized in medical writing for literature searches, evidence synthesis, draft creation, summary, language editing, reference analyses, and manuscript preparations. Evidence on the relative performance, reliability, and maturity of different tools is often fragmented. This review aimed to present a function-based comparison of selected global and Indian or India-focused tools relevant to the medical-writing process. The applications, underlying technologies, benefits, limitations, evidence maturity, and contextuality in the Indian setting were described. The technologies include natural language processing, machine learning, generative artificial intelligence, large language models, retrieval-augmented generation, and AI-assisted evidence analysis tools. While the use of AI can enhance efficiency and reduce some burdensome processes, hallucination, fake references, biases, poor reproducibility, privacy concerns, limited contextual understanding, and lack of transparency hinder autonomous use. The novelty of this review includes the provision of a Global–Indian perspective. Thus, AI needs to be considered an assistant requiring human intervention, scientific and ethical safeguards, and further research to develop standardized tool-specific frameworks for evaluations.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare and Education
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"AI in Medical Writing: A Comparative Analysis of Global and Indian Tools" — Chavan Nikita, Pranav Kulkarni, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS