Since the advent of ChatGPT, researchers have rapidly adopted generative artificial intelligence (AI) for academic work, with monthly use reported by 69.4% of natural science researchers and 51.2% of medical researchers. This educational article surveys AI tools for literature search and trend analysis, study-oriented article organization, and manuscript drafting and editing, while emphasizing that these tools complement—not replace—critical reading and standard database searches. For discovery and mapping, Research Rabbit and Connected Papers visualize related papers through citation links or content similarity, while Consensus summarizes the direction and strength of evidence addressing a focused research question. Elicit and SciSpace can extract methods and conclusions into structured tabular summaries to support scoping and gap identification, and STORM can generate knowledge maps for topic exploration; Liner offers research agents to support hypothesis generation and literature review. To extend reference-management workflows, the article proposes downloading relevant PDFs, uploading them to a large language model, extracting predefined fields (e.g., design, participants, interventions, outcomes, key statistics, limitations, and DOI) into a CSV file, and importing the output into a Notion database for tagging and tracking reading status. For writing support, SciSpace and Liner provide outline generation, citation assistance, and peer review style checks, whereas Paperpal, Wordvice.ai, and DeepL focus on grammar, paraphrasing, and translation, and Scite contextualizes citations by identifying whether they are supporting or contrasting. Key cautions include manual verification of AI outputs, awareness of English-language bias, avoidance of reliance on a single tool, and protection of manuscript confidentiality; authors must disclose AI use and remain accountable for accuracy. When used judiciously, these tools can streamline screening, summarization, and revision without eroding scholarly judgment.
Joon Seo Lim (Mon,) studied this question.
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