Seedlabs

Standardized Disease Taxonomy Database

A structured digital reference system that categorizes diseases by proximate cause, genus, and species to standardize medical diagnosis and treatment mapping.

PsychologyBody Image and Dysmorphia Studies
Medical Diagnostic Software Companies

Concept

A specialized medical database that moves away from symptom-based grouping toward a causal taxonomy. It organizes diseases into natural classes based on their proximate causes, providing a hierarchical structure (Order $\rightarrow$ Genus $\rightarrow$ Species) that links each specific disease directly to its corresponding method of cure and pharmacological intervention.

Why now

The provided text [0] demonstrates a systematic approach to the 'catalogue of diseases' based on natural classes and proximate causes, paired with a corresponding 'materia medica' for cures. Digitizing this taxonomic approach allows modern clinicians to map complex pathologies to specific causal origins more efficiently than unstructured symptom lists.

AI assessment

Backed by 1 paper46

A high-risk attempt to digitize an obsolete 18th-century medical taxonomy that ignores 200 years of genomic and molecular progress.

Evidence strength
1/5
The idea relies on a single historical text ('Zoonomia') whose medical theories have been superseded by modern pathology and germ theory.
Market pull
2/5
While diagnostic software is a huge market, there is no urgency for clinicians to adopt a causal taxonomy based on pre-modern biological laws.
Novelty & moat
2/5
Standardized taxonomies (ICD-11, SNOMED CT) already exist and are far more comprehensive and scientifically valid.
Feasibility
4/5
Digitizing a book into a database is technically trivial, though the resulting product would be medically useless.
Wedge clarity
2/5
The 'wedge' is a general reference system rather than a specific tool solving a current clinical pain point.
Simplicity / focus
4/5
The product is a simple database, avoiding the 'platform' trap, but lacks a viable purpose.

Scored by AI against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity). A prior estimate to compare ideas before real-world signal arrives.

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Who benefits

  • Allows them to navigate a structured hierarchy of diseases to find the most accurate causal diagnosis and associated cure.

  • Provides a structured map of which 'materia medica' (medicines) are linked to specific disease species, aiding in targeted drug discovery.

Research it builds on

  1. Zoonomia, or, The Laws of Organic Life
    Erasmus Darwin · 2024 · 463 citations
    All ideas from this paper →

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