Clinical Decision Support for Integrative Medicine

Every recommendation traced to real evidence

AI-powered clinical decision support that grounds every integrative medicine recommendation in scored, verifiable clinical claims. Built for physicians who demand rigor.

Top-3 Diagnostic Accuracy
91.7%
Hammoud et al. 400-vignette benchmark
Top-1 Accuracy
78.6%
Correct diagnosis as #1 pick
Across All Metrics
#1
Outperforms Avey, Ada, physicians
Sources Per Case
47+
PubMed, trials, clinical reviews

Built for clinical rigor

Not another chatbot. A structured clinical reasoning pipeline with full auditability.

Claim Knowledge Objects

Clinical literature is decomposed into scored, policy-tagged claims — not raw text chunks. Every claim has an evidence tier and quality score.

Diagnostic Reasoning

Multi-hypothesis differential diagnosis with ICD-10 specificity. 4–6 ranked hypotheses per case, each with supporting evidence chains.

Integrative Medicine Recommendations

Integrative medicine recommendations based on our proprietary knowledge base — dosing context, personalized contraindications, and regulatory status.

Safety Validation

Every recommendation passes clinical safety checks: drug interactions, allergies, contraindications, and regulatory flags before reaching you.

Knowledge Graph

Entities and relationships extracted across our entire knowledge corpus and applied to your own patient cases — clinical concepts connected across the integrative medicine domain.

Literature Search

Our proprietary medical knowledge base supplemented with real-time PubMed and clinical trial literature.

See the reasoning. Trust the result.

Every analysis shows its work. Here's a real evidence chain from a patient case — anonymized, shown exactly as the platform produced it.

Clinical question

Can this patient take tesamorelin? Will he benefit?

Confidence 78%Human review required
Age
47
Sex
Male
Focus
Longevity / prevention
Chart flag
G6PD deficiency
Ranked diagnostic hypotheses
Macrocytic anemia, unspecified, with iron-overload patternD53.9
50%

Low RBC/HGB/HCT with increased MCV plus elevated iron and ferritin is not typical of iron deficiency. Raises concern for B12/folate deficiency, alcohol-related marrow toxicity, hypothyroidism, liver disease, medication effect, myelodysplasia, or hemolysis. Despite “no symptoms,” this is a clinically significant incidental finding requiring workup before any GH-axis optimization.

  • Patient labs (observational): macrocytosis with anemia and high iron/ferritin
  • Mechanistic: ineffective erythropoiesis (e.g. B12/folate) can raise iron indices
Other acquired hemolytic anemias (possible episodic hemolysis in G6PD deficiency)D59.8
18%

Known G6PD deficiency raises risk of oxidative-triggered hemolysis; anemia is present though hemolysis markers were not provided. Reticulocytosis can artifactually raise MCV; high ferritin can reflect iron recycling post-hemolysis. Needs a hemolysis panel and reticulocyte count.

  • Patient history: confirmed G6PD deficiency
  • Mechanistic: oxidative stress → RBC membrane damage → hemolysis
Hypothyroidism, unspecified (incl. consideration of central hypothyroidism)E03.9
12%

Knowledge base emphasizes thyroid assessment as first-line (TSH + free T4) and notes risk of missed central hypothyroidism. Hypothyroidism can cause macrocytosis and the dyslipidemia/weight changes that often motivate “optimization” therapies.

  • KB (evidence 86/100): first approach is TSH + free T4
  • KB (evidence 82/100): bioactive-TSH concept for primary/central hypothyroidism
Alcoholic / other chronic liver disease causing macrocytosis and hyperferritinemiaK70.9
10%

Macrocytosis and elevated ferritin can occur with alcohol use and liver disease. Lifestyle (alcohol) and LFTs were not provided — a common, high-yield cause to rule in or out.

  • Mechanistic: alcohol/liver injury → macrocytosis + elevated ferritin
Myelodysplastic syndrome, unspecifiedD46.9
6%

Less common at 47, but must be considered with unexplained macrocytic anemia, especially if persistent or with other cytopenias. If anemia persists after nutritional/endocrine/liver/hemolysis causes are excluded, hematology evaluation is indicated.

  • Observational: persistent unexplained macrocytosis warrants MDS evaluation
Treatment recommendations
Defer tesamorelin (GHRH analog) until anemia/macrocytosis and thyroid status are clarified
Evidence: Mechanistic rationale — KB has no tesamorelin-specific evidence for this case

Tesamorelin raises endogenous pulsatile GH → IGF-1, but GH/IGF-1 activation can mask underlying drivers of fatigue/body composition and may be inappropriate with unrecognized disease. The biology to address first is the unexplained macrocytic anemia.

Levothyroxine (T4) only if hypothyroidism confirmed — standard of care, not a peptide
Evidence: Human RCT / observational (standard endocrine therapy)

If hypothyroidism is present, replacing T4 normalizes thyroid signaling, improving erythropoiesis (may help macrocytosis), lipid metabolism, and energy — addressing a root driver that can mimic “low vitality.”

Anonymized from a real patient case, shown exactly as the platform produced it. AI-generated analysis — not a substitute for clinical judgment.

From patient documents to clinical narrative

A structured pipeline, not a black box.

Step 01

Upload Patient Documents

Upload lab results, intake forms, and clinical notes. The system extracts and populates the patient file automatically — no manual data entry.

Step 02

Patient File Auto-Populated

Demographics, symptoms, labs, medications, and allergies structured automatically from uploaded documents. Review and refine as needed.

Step 03

Ask a Clinical Question

Pose a question about the patient. The AI analyzes their data, retrieves evidence, reasons through differentials, and validates safety.

Step 04

Review, Report & Act

Receive a physician-to-physician narrative with the full evidence trail. Download a professional, personalized medical report for your patient — every claim traceable. You make the final call.

Measured against the standard

400 peer-reviewed clinical vignettes. Same dataset. Direct comparison.

Top-1 AccuracyCorrect diagnosis as the #1 pick

Integrative Medicine AI
78.6%
Avey (Bayesian)
67.5%
Physicians (avg)
61.2%
MedAsk (GPT-4o)
58.3%
Ada
54.2%
K Health
27.8%
Buoy
26.0%
WebMD
24.5%

Top-3 AccuracyCorrect diagnosis within the first 3 picks

Integrative Medicine AI
91.7%
Avey (Bayesian)
87.3%
MedAsk (GPT-4o)
78.7%
Physicians (avg)
72.5%
Ada
71.3%
WebMD
40.7%
Buoy
40.0%
K Health
39.0%

Top-5 AccuracyCorrect diagnosis within the first 5 picks

Integrative Medicine AI
91.7%
Avey (Bayesian)
90.0%
MedAsk (GPT-4o)
82.0%
Ada
76.2%
Physicians (avg)
72.9%
WebMD
50.2%
K Health
41.5%
Buoy
40.0%

Source: Hammoud et al. 2024 (JMIR AI), SymptomCheck Bench 2024. All systems evaluated on the identical 400 peer-reviewed clinical vignettes. See full methodology →

See it in action

Schedule a 30-minute demo and walk through a real clinical case with our team. No commitment, no sales pressure.