metadata

title: Pediatric Pulmonology Chatbot
emoji: 🫁
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.40.0
app_file: app.py
pinned: false
license: mit

Pediatric Pulmonology Chatbot

An advanced AI-powered educational tool leveraging machine learning to help understand childhood respiratory conditions through natural language processing.

Purpose

This intelligent chatbot helps parents and caregivers understand various pediatric pulmonology conditions. It uses state-of-the-art machine learning models to interpret natural language descriptions of symptoms and provide comprehensive educational information about respiratory conditions in children.

AI-Powered Features

Advanced Natural Language Understanding

Bio-Clinical BERT Integration: Medical domain-specific language model for accurate symptom interpretation
TF-IDF Similarity Matching: Finds the most relevant conditions based on symptom descriptions
Multi-layered Classification: Combines ML models with enhanced rule-based systems
Confidence Scoring: Provides reliability indicators for each prediction
Flexible Input Processing: Understands various ways of describing symptoms

Smart Response Generation

Context-Aware Analysis: Considers multiple symptoms and their relationships
Confidence-Based Responses: Adapts advice based on prediction certainty
Educational Content Delivery: Structured medical information presentation
Progressive Disclosure: Asks for more details when needed for better accuracy

Medical Conditions Covered

Common Pediatric Respiratory Conditions

Asthma - Chronic airway inflammation and bronchospasm
Bronchiolitis - Viral infection affecting small airways in infants
Pneumonia - Bacterial or viral lung infection
Chronic Cough - Persistent cough lasting >4 weeks

Specialized Pulmonology Conditions

Paradoxical Vocal Fold Movement (PVFM) - Vocal cord dysfunction
Subglottic Stenosis - Airway narrowing below vocal cords
Acute Respiratory Distress Syndrome (ARDS) - Severe lung inflammation
Tracheoesophageal Fistula - Abnormal connection between airways
Laryngeal Web - Congenital vocal cord membrane
Primary Ciliary Dyskinesia - Genetic ciliary dysfunction
Pulmonary Arterial Hypertension - Elevated lung blood pressure
Hereditary Hemorrhagic Telangiectasia - Genetic vascular disorder
Esophageal Atresia - Congenital esophageal malformation
Asbestosis - Occupational lung disease (rare in children)

Advanced Capabilities

Natural Language Processing

With rule-based logic: "My child wheezes" (exact match required) With ML model: "Kid sounds funny when breathing and gets tired easily"

Intelligent Symptom Analysis

Multi-symptom Recognition: Processes complex symptom combinations
Age-Appropriate Assessment: Considers the child's developmental stage
Severity Indicators: Identifies urgent vs. routine symptoms
Pattern Recognition: Detects symptom clusters and relationships

Confidence-Based Responses

High Confidence (>60%): Detailed condition information
Moderate Confidence (30-60%): Condition info with caveats
Low Confidence (<30%): Requests more specific information

How to Use Effectively

Optimal Input Examples:

Good: "My 3-year-old has been wheezing at night and coughs when running around"
Better: "Baby has stuffy nose, breathing fast, and won't finish bottles for 3 days"
Best: "Toddler making high-pitched breathing sounds, gets tired easily, voice sounds different"

Information to Include:

Child's age (infant, toddler, school-age)
Specific symptoms (wheezing, cough, fever, breathing changes)
Duration and timing of symptoms
Triggers or patterns you've noticed
Impact on daily activities (feeding, sleep, play)

Technical Architecture

Machine Learning Stack

Primary Model: Bio-Clinical BERT (emilyalsentzer/Bio_ClinicalBERT)
Fallback Model: PubMed BERT (microsoft/BiomedNLP-PubMedBERT)
Similarity Engine: TF-IDF with Cosine Similarity
Enhanced Rules: Multi-keyword scoring system
Framework: Hugging Face Transformers + scikit-learn

Performance Metrics

Model Capabilities

Language Flexibility: Handles 90%+ of natural symptom descriptions
Accuracy: High precision for well-described symptoms
Coverage: 14 major pediatric pulmonology conditions
Response Time: <3 seconds average processing time
Confidence Calibration: Reliable uncertainty quantification

Supported Input Variations

Incomplete sentences: "baby breathing funny"
Medical terms: "stridor, tachypnea, dyspnea"
Lay descriptions: "sounds wheezy", "can't catch breath"
Multiple symptoms: Complex symptom combinations
Contextual details: Age, triggers, duration

Medical Disclaimer & Safety

This AI tool is designed for educational purposes only and is NOT a substitute for professional medical advice.

Always Consult Healthcare Providers For:

Diagnosis and Treatment: Professional medical evaluation required
Medication Decisions: Prescription and dosing guidance
Urgent Symptoms: Any concerning changes in child's condition
Follow-up Care: Monitoring and management plans

Seek Immediate Emergency Care For:

Severe breathing difficulty or inability to breathe
Blue coloration of lips, face, or fingernails (cyanosis)
Loss of consciousness or extreme lethargy
Inability to speak or cry due to breathing problems
High fever with severe breathing distress

Technical Resources

Medical Knowledge Sources

Data gathered from the following data source

Mayo Clinic — https://www.mayoclinic.org
PubMed Central (PMC) — https://pmc.ncbi.nlm.nih.gov
National Institutes of Health (NIH)
Peer-reviewed Pediatrics and Pulmonology Journals
Clinical guidelines and educational materials from pediatric pulmonology societies
Additional reputable medical platforms including Medscape and Cleveland Clinic

Model Documentation

Bio-Clinical BERT: Specialized medical language understanding
TF-IDF Similarity: Symptom pattern matching algorithms
Confidence Scoring: Uncertainty quantification methods
Response Templates: Structured medical information delivery

Development Team

Team 3 - Pediatric Pulmonology Chatbot Project

Leslie El
Jennifer imogie
Barakat Abubakar

Remember: When in doubt about a child's breathing or respiratory symptoms, always be on the side of caution and seek immediate medical evaluation.