EBPcharlie

Evidence-based practice, with the trail still visible.

EBPcharlie helps clinicians search PubMed, shape PICO, score trust, and turn research into something you can actually use.

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PubMed search Real-time PICO 30+ trust signals Audio output PWA-ready

Working app
Evidence workflow
Clinician review required

EBPcharlie live preview

Search, discover, history, trust score, recommendation output, podcast generation, and a cleaner route from question to evidence.

Evidence flow

QuestionPICO-ready PubMedrelevant studies Trust30+ signals Recommendationclear action

The problem

Manual evidence review is still slow, fragmented, and easy to lose under pressure.

Clinicians still jump between PubMed tabs, abstracts, notes, and ad hoc quality judgments. The result is familiar: too many results, too little structure, and too much pressure on the final call.

EBPcharlie compresses that workflow into a clearer path. Ask one question. Retrieve the literature. Score trust. Synthesize. Then act with more context and less friction.

It is not trying to replace evidence-based practice. It is trying to make it easier to use well.

EBPcharlie 2.0

More structure, less noise, and no hidden reasoning.

The newer layer brings ClinicalBERT support, real-time PICO extraction, clinical scoring, advanced quality assessment, podcast output, and a PWA workflow into the same research surface.

ClinicalBERT

Clinical language understanding.

ClinicalBERT support helps the system interpret clinical language, population details, intervention terms, and outcome signals with more precision.

Quality

Quality assessment.

Bias detection, study design classification, and methodology checks help separate stronger evidence from weaker signals.

Clinical scoring

Clinical relevance and decision support.

The scoring layer considers whether the evidence is usable for real clinical decisions, not only whether it looks strong on paper.

Accuracy

95%+ analysis accuracy target for supported flows.

The product interface presents a high accuracy target for supported clinical analysis flows. The evidence trail remains visible so users can still inspect the reasoning.

How it works

Ask, search, score, synthesize, act.

This is the core product logic: one clinical question becomes a structured evidence answer with the trust signals still visible.

Ask

Start with one question.

EBPcharlie starts where real work starts: a clinical question that can be shaped into PICO before anything else happens.

Search PubMed with intent.

The search layer is built for clinical questions, PICO logic, publication filters, and relevance, not generic keyword guessing.

Score

Score the evidence.

Instead of hiding behind one answer, EBPcharlie shows the signals behind it: study type, venue, method, sample quality, bias, and relevance.

Synthesize

Turn papers into a synthesis.

The output becomes a recommendation, summary, limitations view, and implementation guide instead of a wall of abstracts.

Act

Keep the trail visible.

The final step is not blind automation. It is a clearer recommendation with source context, scoring logic, and uncertainty still visible.

Enhanced clinical search

The search screen starts from the question, not keyword guessing.

The analysis form supports a clinical question, flexible PICO requirements, ClinicalBERT analysis, publication type filters, professional background, and date ranges. The point is to shape the search before the evidence is scored.

Real-time PICO analysis shows completeness across population, intervention, comparison, and outcome, so the user can improve the question before relying on the result.

Flexible PICO requirements ClinicalBERT analysis Publication type filter Professional background Start and end year filters Real-time PICO completeness

Core features

A research workflow built for speed, scrutiny, and clinical use.

The point is not to flood the screen with more data. The point is to make the evidence legible enough to use and transparent enough to trust.

Clinical PubMed search.

Searches are built for clinical questions, PICO structure, publication filters, and evidence retrieval. This is the front door.

Trust

Three-layer trust scoring.

Venue vetting, manuscript triage, and deeper content checks are combined into one readable trust layer that stays auditable.

Question logic

PICO extraction and alignment.

Population, intervention, comparison, and outcome are identified in real time so the question stays clinically useful.

Hierarchy

Evidence hierarchy classification.

Systematic reviews, randomized trials, cohort studies, and weaker study types are separated so the user can scan quality quickly.

Synthesis

Clinical synthesis, not just summaries.

The answer is shaped around what matters in practice, not around abstract summaries alone. It stays useful without pretending certainty.

Statistics

Statistical synthesis when needed.

Effect sizes, heterogeneity, and decision-useful signals such as NNT or NNH can be surfaced when the evidence needs a deeper pass.

Scoring

Clinical relevance scoring.

The system looks at real-world applicability, not only publication strength, so the output is easier to use in practice.

Implementation

Implementation guidance.

The output can separate immediate use, secondary consideration, and longer-term interpretation instead of treating every finding the same way.

Limits

Limits stay visible.

EBPcharlie does not only tell you what looks strong. It also shows where evidence is thin, mixed, or not ready for action.

Verification

Reference verification.

The verification layer reduces bad references, broken claims, and stitched-together source errors. Trust has to be earned in the open.

Audit depth

Deeper article analysis.

When a paper matters, the system can go beyond summary and inspect quality, bias, and weak points more carefully.

Compass

Evidence compass.

Instead of a closed score, the user gets a clearer sense of how strong, consistent, and clinically usable the evidence is.

Output

PDF and audio output.

Research output can be turned into shareable documents or podcast-style audio so clinicians and students can review findings in a different format.

App access

Installable PWA access.

EBPcharlie can be installed for quicker access, a cleaner research workflow, and a more focused entry point than a browser tab.

Outputs

Analysis, scoring, and audio formats in one evidence workflow.

EBPcharlie is not only a search page. It is a research workflow that can turn the same evidence base into a structured review, a recommendation, a score layer, and an audio learning format.

Synthesis

Complete evidence review.

The output brings search results, trust signals, hierarchy, limitations, and recommendations into one readable flow.

Podcast

Audio podcast generation.

Research findings can be converted into an audio format for review, teaching, or clinical learning without losing the evidence structure.

Voices

Multiple voice clinical discussion format.

The podcast layer is designed to feel like a professional clinical discussion, not a flat reading of a summary.

Feedback

User feedback loop.

Ratings and comments help improve search quality, trust assessments, interface clarity, and the features clinicians actually need.

Glass box transparency

The scores should be inspectable, not magical.

EBPcharlie should not hide behind a single summary score. The whole point is that users can inspect the hierarchy, the signals, and the context that shaped the recommendation.

That is the difference between a clinical evidence system and a glossy answer engine. If the trust layer cannot be audited, it should not be trusted.

This is also what separates EBPcharlie from a normal manual review and from lighter search tools. The goal is not only retrieval. The goal is structured scrutiny.

Research verification layer

Nagomi sits underneath the evidence mindset.

EBPcharlie is the product surface. Nagomi is closer to the command-line research layer: search PubMed, structure the question, verify references, inspect a paper, and export the trail.

That matters because evidence work should not only produce an answer. It should leave enough structure behind to check the answer.

View Nagomi

Example use

/nagomi:search chronic low back pain exercise
/nagomi:verify references.pdf
/nagomi:analyze 34580864

Premium depth

Built for clinicians first, but useful wherever evidence has to become action.

Clinicians

Clinicians first.

People who need a faster route from question to a structured evidence answer without losing the evidence trail.

Researchers

Researchers.

The system compresses retrieval, hierarchy, and trust signals so more time can go into the harder interpretive work.

Students

Students.

EBPcharlie helps make evidence appraisal less abstract by showing why one source or recommendation deserves more trust than another.

Technical architecture

Clinical language, retrieval, and evidence infrastructure underneath.

Under the surface, EBPcharlie is shaped around clinical language models, PubMed retrieval, Semantic Scholar context, PICO structure, trust assessment, and a product layer that keeps the research flow usable instead of overwhelming.

ClinicalBERT integration PubMed API Semantic Scholar Tiered clinical analysis PICO framework Trust scoring layer PWA-ready product surface

Ready when you are

Start with one clinical question. Search less, score more, and keep the evidence trail.

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Built for clinicians, researchers, and students who want a faster answer without losing the evidence trail.