For clinicians with datasets

Your next paper
already exists.

The data has never been the bottleneck. The research protocol has been. AI just made that bottleneck smaller than it has ever been — if you know how to use it without making the mistakes that invalidate the work.

4
Manuscripts from
one clinical dataset
1 wk
From dataset to
publication-ready protocol
3 yrs
Refining this
framework in clinical practice

The exact process I use to go from a clinical observation to a protocol.

Most clinicians have data. Very few have the time or the training to turn that data into a structured research protocol before the moment passes. AI has changed that equation — but only if it is used in the right sequence, with the right guardrails.

I'll send you the framework I use. Four steps. Real prompts. The mistakes to avoid. No theory without practice.

01
PICO definition AI-assisted Turn a clinical hunch or M&M observation into a structured, defensible research question.
02
Study design AI-assisted Match your data to the right design. Identify confounders, variables, and subgroup logic before you collect anything extra.
03
Statistical analysis plan AI-assisted Define your tests, thresholds, and subgroups before you look at the results. This goes into your ethics application.
04
Ethics application draft AI-assisted Background, rationale, significance — the boilerplate sections that take the longest. AI drafts them from steps 1–3.

What AI cannot do: verify its own references, know your local ethics board requirements, compensate for gaps in your data, or determine what question is worth asking. Clinical judgment is irreplaceable. This framework is a tool for clinicians — not a substitute for one.

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Framework coming to your inbox within 24 hours. If you have a specific dataset in mind, reply to that email — I read every one.

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EK

Dr. Ehsan M. Kiani

MCPS · FCPS · Consultant Interventional Radiologist

Consultant Interventional Radiologist at Hearts International Hospital, Rawalpindi, and founding trustee of Aab-e-Rawan Trust. I lead what is likely the first formally documented online hepatobiliary MDT in Pakistan, between Hearts International and Ayub Teaching Hospital, Abbottabad.

Over three years I have used AI as a thinking partner in clinical research — taking datasets through a repeatable process from raw data to manuscript. DataCraft is how I teach that process to other clinicians. Small cohorts, real datasets, no theory without practice.

LinkedIn datacraft.com.pk