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Differential Diagnosis

Expand and refine your differential diagnosis skills using structured approaches and AI assistance.

Overview​

This module focuses on preventing premature closure and building comprehensive differentials (DDx). You'll learn to use multiple DDx generation strategies, compare hypotheses systematically, and calibrate your diagnostic confidence.

Module Structure​

The module is split into 4 main tabs:

  1. Expand DDx — Generate diagnoses you might have missed.
  2. Generate Questions — Learn which questions narrow the differential.
  3. Compare Hypotheses — Systematically compare competing diagnoses.
  4. Matrix Analysis — Advanced structured comparison.

Tab 1: Expand Your Differential​

Goal​

Generate additional diagnoses based on the patient's findings.

Input Fields​

  1. Symptoms (Subjective): HPI-style description (e.g., "Fever, cough, and dyspnea for 3 days").
  2. Clinical Signs (Objective): Vitals and physical exam (e.g., "Temp 39°C, crackles at right base, SpO2 92%").
  3. Initial Diagnoses: Your current list of suspects (one per line).

AI Output​

The AI suggests additional diagnoses categorized by suspicion level:

  • 🔴 High Suspicion: Strong hypotheses based on the data.
  • 🟡 Moderate Suspicion: Diagnostic possibilities.
  • 🟢 Low Suspicion (But "Can't Miss"): Serious diagnoses that must be excluded, even if unlikely.

Tab 2: Generate DDx Questions​

Learn to ask questions that discriminate between hypotheses. The focus is identifying what "rules in" or "rules out" each diagnosis.

Example: For a cough complaint, the system might suggest asking about "sick contacts" (epidemiology) or "night sweats" (red flags for malignancy/TB).

Tab 3: Compare Hypotheses​

Compare competing hypotheses to identify key discriminators.

Difficulty Levels​

  • 🟢 Basic: Simple presentations (e.g., appendicitis vs cystitis).
  • 🟡 Intermediate: Moderate complexity (e.g., MI vs angina vs pericarditis).
  • 🔴 Advanced: Complex or atypical cases.
  • ⚫ Expert: Challenging cases with rare diagnoses.

Tab 4: Matrix Analysis (Advanced)​

Build a matrix comparing clinical findings against hypotheses.

How it works:

  • Rows: Clinical findings.
  • Columns: Diagnostic hypotheses.
  • Cells: Mark as SUPPORTS (✅), NEUTRAL (⚪), or REFUTES (❌).

The goal is to identify the strongest discriminator — the finding that best separates the hypotheses.

caution

Expert Tip: Don't try to list everything. Focus on diagnoses that would change your immediate management if confirmed.