Medical Dataset Analysis & Statistics
This comprehensive analysis covers three key medical datasets, providing detailed insights into their structure, content, and distinctive characteristics.📊 Dataset Overview
Our analysis covers three distinct medical datasets, each serving different purposes in the healthcare AI domain:General Medical Instruction
1,867 entries focused on educational medical content with concise questions and detailed explanations
Evaluation Medical Instruction
3,324 entries designed for medical exams with multiple-choice format and brief answers
GenMedGPT-5k
3,088 entries simulating patient-doctor dialogues with focus on pain management
🔍 Detailed Statistical Comparison
Text Length Analysis
| Dataset | Entries | Avg Instruction | Avg Input | Avg Output | Input-to-Output Ratio |
|---|---|---|---|---|---|
| General Medical | 1,867 | 4.0 words | 17.10 words | 33.10 words | 0.52 |
| Evaluation Medical | 3,324 | 46.0 words | 30.05 words | 2.67 words | 11.25 |
| GenMedGPT-5k | 3,088 | 15.0 words | 23.04 words | 44.76 words | 0.51 |
The Evaluation Medical Dataset has the highest input-to-output ratio (11.25), indicating it’s designed for multiple-choice or short-answer testing with lengthy questions but very brief responses.
Top Medical Terms by Dataset
- General Medical
- Evaluation Medical
- GenMedGPT-5k
Input Field Terms:
syndrome(8.94%)disease(6.37%)carcinoma(3.00%)infection(2.46%)tumor(1.98%)
characterized(high frequency)type(high frequency)disease(high frequency)syndrome(high frequency)cells(high frequency)
🎯 Key Distinctive Features
1
General Medical Dataset
Educational Focus
- Balanced medical terminology distribution
- Moderate input complexity with detailed explanations
- Strong emphasis on syndrome and disease classification
- Perfect for medical education and reference systems
2
Evaluation Medical Dataset
Examination Format
- Extremely high input-to-output ratio (11.25x)
- Long, complex questions with very short answers
- Frequent use of “except” indicating multiple-choice format
- Ideal for medical board preparation and testing systems
3
GenMedGPT-5k Dataset
Clinical Dialogue
- 34.62% pain-related content - extraordinary specialization
- Patient-doctor conversation simulation
- Longest output responses (44.76 words average)
- Optimal for conversational AI and patient consultation systems
📈 Medical Condition Prevalence
Cross-Dataset Condition Analysis
Pain Management Focus
Pain Management Focus
GenMedGPT-5k shows extraordinary specialization:
pain: 34.62% (vs. 0.37% in General Medical, 3.09% in Evaluation)- This represents a 90x higher pain focus compared to other datasets
- Indicates specialized use case for pain management applications
General Medical Conditions
General Medical Conditions
Balanced distribution across datasets:
syndrome: 8.94% (General), 4.87% (Evaluation), 1.42% (GenMedGPT)disease: 6.37% (General), 6.17% (Evaluation), 2.81% (GenMedGPT)blood: 1.50% (General), 3.22% (Evaluation), 3.33% (GenMedGPT)
Specialized Terms
Specialized Terms
Dataset-specific terminology patterns:
- General Medical: High carcinoma/tumor focus (medical education)
- Evaluation Medical: Balanced clinical terms (exam preparation)
- GenMedGPT-5k: Patient symptom language (consultation simulation)
🔗 Correlation Insights
Input-Output Length Relationships
General Medical
Correlation: 0.1423
Weak positive correlation between question length and answer detail
Weak positive correlation between question length and answer detail
Evaluation Medical
Correlation: 0.0392
Nearly no correlation - consistent short answers regardless of question length
Nearly no correlation - consistent short answers regardless of question length
GenMedGPT-5k
Correlation: 0.2587
Strongest correlation - longer patient questions receive more detailed responses
Strongest correlation - longer patient questions receive more detailed responses
The GenMedGPT-5k dataset shows the most natural conversation pattern where complex patient concerns (longer inputs) typically receive more comprehensive medical responses (longer outputs).
🎯 Dataset Selection Guide
Choose the Right Dataset for Your Use Case
- Medical Education
- Exam Preparation
- Patient Consultation AI
- Comprehensive Coverage
Recommended: General Medical Dataset
- Balanced medical terminology
- Educational question-answer format
- Detailed explanations and definitions
- Covers wide range of medical conditions
📋 Quality Metrics Summary
Content Diversity
Excellent
25+ medical specialties covered across datasets
25+ medical specialties covered across datasets
Format Variety
High
Educational, examination, and conversational formats
Educational, examination, and conversational formats
Specialization
Strong
Each dataset serves distinct use cases effectively
Each dataset serves distinct use cases effectively
Correlation
Varied
Different input-output relationships match intended use
Different input-output relationships match intended use