Artificial Intelligence Tools for Academics in Medicine

  • Somashekhar Nimbalkar Professor and Head, Department of Neonatology, Pramukhswami Medical College, Bhaikaka University, Karamsad, Anand, Gujarat, India.
Keywords: Artificial Intelligence,; Medicine,; Applications;, Research;, Academics

Abstract

The emergence of ChatGPT in December 2022 has sparked signifi cant interest in Arti fi cial Intelligence (AI) across the public and academic communiti es. However, AI’s applicati ons in research extend far beyond
ChatGPT, off ering tools that can enhance various stages of the research process, from idea generati on to disseminati on. Research Rabbit is an AI assistant that helps researchers discover and organize academic papers into shareable collecti ons, fostering a sense of community and making literature explorati on more effi cient and collaborati ve. SciSpace (formerly Typeset) simplifi es the understanding of complex research papers by providing clear explanati ons and off ering tools for literature reviews, citati on generati on, and document formatting. This saves researchers valuable ti me and streamlines the research writi ng process. Scite Assistant leverages Smart Citati ons to provide context on how articles are cited. It off ers insights into whether a citati on supports or contrasts the referenced work, helping researchers assess the credibility and impact of studies.
Consensus is an AI-driven search engine that fi nds relevant papers based on research questi ons, providing summaries and a consensus meter to quickly gauge the overall stance on a specifi c topic. Elicit automates literature reviews by identi fying relevant papers, summarizing key informati on, and off ering tools for brainstorming, argument structuring, and text classifi cati on. These AI tools signifi cantly enhance producti vity and effi ciency by aiding in the organizati on, analysis, and understanding of academic research. While they off er substanti al benefi ts, using them alongside human experti se and criti cal thinking is important, as AI is not infallible and may have limitati ons, such as data biases and ethical concerns.

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Published
2024-09-07