How it works

Why guess when you have evidence?

AI gives answers. We show the scientific source. Inciteful Med grounds every response in peer-reviewed research, so patients can understand their options and make informed decisions.

Ask a Question See how it works

Understanding Your Diagnosis: Mast Cell Activation Syndrome (MCAS)

Your recent evaluations and tests strongly support a diagnosis of Mast Cell Activation Syndrome (MCAS). MCAS is characterized by recurrent episodes involving multiple mediators, affecting at least two organ systems. ^[1][2][3]

Your Recent Test Results Confirm MCAS

During your symptomatic episode on April 4, 2025, your tryptase rose from 4.1 ng/mL to 6.9 ng/mL, meeting the widely accepted "20% + 2 rule." ^[4][5]

Using the Right Criteria for MCAS.

Current allergy and asthma reports 2024; (24(2):3 9-51). doi:10.1007/s11882-024-01126-0

Excerpt from paper

PURPOSE OF REVIEW The current article aims to provide a comprehensive update on diagnostic criteria for mast cell activation syndrome (MCAS), addressing challenges in diagnosing and classifying MCAS and its variants.

Answers grounded in scientific evidence

01 / The corpus

The full medical literature, refreshed every day.

An LLM has a knowledge cutoff. We don't. Every day we re-sync with PubMed, so the research you see reflects what's been published, not what was true when a model finished training.

42M+

Articles & abstracts indexed from PubMed

1.9M

New papers added in the last year

~2/min

New papers indexed worldwide

Daily

Index refresh, no knowledge cutoff

02 / LLM vs. Inciteful Med

Two fundamentally different machines.

ChatGPT and similar tools are generators. They produce plausible text. Inciteful Med is a retriever. It finds the underlying evidence and shows it to you.

Dimension

General LLM

Inciteful Med

01 Knowledge cutoff

General LLM

× Frozen at training date. Months or years out of date.

Inciteful Med

✓ None. Index refreshed daily from live PubMed.

02 Source of answers

General LLM

× Statistical patterns in training data.

Inciteful Med

✓ Direct retrieval from peer-reviewed papers.

03 Citations

General LLM

× Often invented. Plausible-looking DOIs that don't exist.

Inciteful Med

✓ Every claim links to a real, verifiable paper.

04 Fabrication risk

General LLM

× High. Will confidently produce false claims.

Inciteful Med

✓ Low. If the literature doesn't support it, we don't say it.

05 Transparency

General LLM

× Black box. Can't show why it said what it said.

Inciteful Med

✓ Every sentence maps to its source.

06 Method

General LLM

× Generation. Predicting the next likely token.

Inciteful Med

✓ Retrieval. Finding and summarizing actual evidence.

03 / The system, in detail

From your question to a cited answer.

01

Expand the question

You don't need the perfect prompt. We expand your plain-language question into the 20+ related clinical sub-questions a thorough answer would cover, including the ones you didn't know to ask, and map them to the concepts and MeSH terms the medical literature is indexed under.

02

Retrieve from the live index

Search PubMed's 42M+ articles in real time. We pull explicit snippets that answer each sub-question, often hiding inside papers about something else, plus related work. No frozen training snapshot.

03

Verify and rank

Use citation meta-analysis to verify each claim and rank by how directly it answers your question, recency, and the strength of the evidence.

04

Synthesize in plain terms

Produce a plain-language answer where every sentence maps to a citation, with the original excerpt and link preserved. No claim appears without a paper behind it.