AIMEDICINEUPDATE.COM 8/4/2025
For resident physicians and early-career clinicians, conducting research often feels like an uphill battle. Time is limited, administrative burdens are high, and academic mentorship may not always be easily accessible. Yet the desire to contribute to the scientific community and improve patient care remains strong.
Fortunately, artificial intelligence (AI)—especially general-purpose tools like ChatGPT or Microsoft Copilot—is opening new doors for clinicians to participate in meaningful research without requiring advanced technical skills or extra hours in the day. Whether you’re developing a hypothesis, conducting a literature review, preparing your IRB submission, or writing up results, AI can help streamline nearly every step of the research process.
From Clinical Curiosity to Research Question
All clinical research begins with a question, often sparked during a patient encounter or while reviewing cases. But translating curiosity into a viable, focused research question can take time and guidance—two resources that may be in short supply.
This is where AI can help. By engaging in a conversational exchange with a tool like ChatGPT, you can explore potential study questions based on common clinical challenges, recent guideline changes, or unmet needs in patient care. For example, you might prompt, “What are emerging research gaps in inpatient diabetes management?” or “Suggest feasible retrospective study topics using hospital EHR data.”
Through iterative dialogue, AI can help you refine a broad interest into a researchable, actionable question.
Literature Review Made Smarter and Faster
The literature review is one of the most labor-intensive parts of any research project. Sifting through dozens or hundreds of abstracts to assess relevance can be exhausting, especially after clinical hours. AI can significantly ease this burden.
You can ask AI to help summarize key findings from abstracts, compare methodologies between studies, or extract common limitations across a body of literature. For example, by pasting a group of abstracts into your AI assistant, you can request a synthesis of study types, outcomes measured, or risk-of-bias indicators.
But AI can do more than summarize. It can also help you construct a precise PubMed search using MeSH (Medical Subject Headings) terms a capability that’s particularly valuable if you’re unfamiliar with structured database querying.
Tip: Use AI to Build PubMed MeSH Searches
Use AI to Build PubMed MeSH Searches
Struggling to create a precise PubMed search? AI tools like ChatGPT can help you build structured queries using Medical Subject Headings (MeSH) and Boolean logic.
Just provide your research question in natural language, and ask the AI to:
- Identify relevant MeSH terms
- Combine them with Boolean operators (AND/OR)
- Format the query for PubMed
Prompt Template:
“I’m conducting a literature review on the use of [intervention] for [condition] in [population]. Can you generate a PubMed search query using MeSH terms and Boolean operators to help me find relevant articles?”
Example:
“I’m researching the use of low-dose CT scans for lung cancer screening in adults over 50 with a history of smoking. Please create a PubMed search string using MeSH terms.”Once the search string is generated, paste it into PubMed, review the results, and adjust as needed. For systematic reviews, you can also share it with a librarian for expert input.
Drafting IRB Submissions and Protocols
Preparing IRB applications can be one of the most intimidating parts of clinical research, especially for those without prior experience. Fortunately, AI can assist in creating the foundational components of your submission.
You can use AI to draft study rationales, articulate objectives, and generate consent form language all in clear, structured formats. For example, by providing a brief summary of your planned study, the AI can help write sections on inclusion criteria, data collection methods, and ethical considerations. While these drafts will always need review and approval by a faculty mentor or IRB office, they offer a valuable head start.
Cleaning and Preparing Data Without Coding
Once your data is collected—whether from chart reviews, patient surveys, or registries—it usually requires cleaning. This may include renaming columns, standardizing units, handling missing values, or identifying outliers. These steps can be daunting for clinicians who aren’t familiar with data science tools.
Using AI, you can ask for help with data organization even if you’re working in Excel. For example, a simple prompt like, “How do I identify duplicate rows in my spreadsheet and remove them?” or “Explain how to categorize patients by diagnosis codes in my dataset,” can yield step-by-step guidance or suggested formulas. If you’re comfortable using basic statistical software, you can even ask the AI to generate code in R or Python based on your dataset description.
Demystifying Statistical Analysis
Understanding which statistical tests to use—and how to interpret them—is a common barrier to completing a study. But with the help of AI, this step becomes more manageable. You can describe your study design and variables, and ask for advice on appropriate tests: “What statistical test should I use to compare readmission rates between two patient groups?” or “How do I analyze time-to-event outcomes in a retrospective cohort?”
The AI can walk you through assumptions, suggest visualizations (like Kaplan-Meier curves or box plots), and even explain the meaning of p-values, confidence intervals, or regression coefficients. This is particularly helpful when preparing the results section of a manuscript or discussing findings with co-authors.
As always, it’s wise to consult with a biostatistician before finalizing your analysis, but AI can help you feel more confident and prepared for those conversations.
Writing, Editing, and Submitting Your Manuscript
The process of writing a manuscript can be one of the most time-consuming stages of research. Fortunately, this is where general-purpose AI tools shine. With a detailed outline or section summaries, AI can help transform your ideas into polished academic prose. It can suggest transitions, clarify awkward phrasing, and even adjust tone to match your target journal’s style.
You can also use AI to draft cover letters, rephrase your abstract for clarity, or format references. When you’re deciding where to submit, the AI can help identify journal types based on your topic and article type—for example, “Suggest suitable journals for a case-control study on hospital readmissions in heart failure patients.”
Enhancing Collaboration with AI Support
For research teams, AI can also support collaboration. You can use it to summarize meeting notes, draft shared documents, or maintain consistency across contributions from multiple authors. If you’re working with collaborators from different specialties, AI can translate technical terms or rephrase content for cross-disciplinary clarity.
In collaborative writing, AI can also help harmonize tone and formatting, making it easier to merge different writing styles into a cohesive manuscript.
Ethical Best Practices for Using AI in Research
While AI is a powerful tool, it must be used responsibly—especially in academic and clinical contexts. Here are a few guiding principles:
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- Do not input patient-identifiable data into AI platforms, especially those not hosted on secure, institution-approved servers.
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- Verify all AI-generated outputs for accuracy, particularly when summarizing clinical evidence or citing literature.
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- Disclose AI use in your manuscript, especially if it contributed significantly to writing, analysis, or protocol development.
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- Maintain human oversight at all stages—AI is a tool, not a substitute for critical thinking or ethical judgment.
Final Thoughts
AI is not a shortcut to becoming a researcher—but it is a catalyst. For clinicians and trainees who are eager to contribute to clinical science but short on time, tools like ChatGPT and Copilot offer an efficient, low-barrier way to participate in research meaningfully.
By integrating AI into your workflow, you can move from idea to IRB, from analysis to authorship, with greater confidence and less stress.
Whether you’re preparing your first abstract or launching a new project, AI is ready to help. The only question is: what will you research next?