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  Emergency pulmonary embolism pathway for faster, clearer, evidence-based decisions through a simple interactive design.

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  Interactive pulmonary function workflow combining guideline-based interpretation with visual flow-volume loop pattern recognition.

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  Generates personalized AI prompts from smoking history to transform cost data into meaningful health and financial insights.

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  Interactive pneumonia workflow guiding physicians from diagnosis to severity scoring and evidence-based treatment in one clear interface.

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  A curated library of reusable AI prompts that helps physicians solve clinical and educational tasks in seconds.

PulmoCalc – AI-Powered Pulmonary Decision Support

Inspiration

I am a pulmonology resident physician who wanted to solve a daily clinical problem.

Every day, physicians switch between multiple guidelines, calculators, journal articles, and educational resources while caring for patients. This interrupts workflow, wastes time, and increases cognitive load.

I wanted to build one intelligent workspace where pulmonologists could access everything they need in seconds.

That idea became PulmoCalc.

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What it does

PulmoCalc is an AI-powered platform that combines pulmonary education, clinical decision support, and interactive medical calculators in one place.

It includes:

• Evidence-based pulmonary workflows
• Interactive clinical calculators
• Pneumonia severity assessment
• Pulmonary embolism evaluation
• Blood gas (ABG) interpretation
• Pulmonary function test guidance
• Sleep medicine tools
• Educational learning modules
• Rapid bedside clinical references

The platform is designed to support physicians—not replace their clinical judgment.

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How I built it

PulmoCalc was built using OpenAI technologies including ChatGPT, GPT-5.6, Codex, and ChatGPT Sites.

AI was involved throughout the entire development process—from brainstorming ideas and designing the user experience to generating code, refining workflows, debugging, improving the interface, and continuously expanding medical content.

Hundreds of iterative improvements transformed an initial prototype into a practical platform for pulmonologists.

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Challenges

The greatest challenge was translating complex clinical guidelines into intuitive interactive workflows without oversimplifying medical decision-making.

Another challenge was designing a fast and clean interface that remains useful during real clinical practice.

Maintaining scientific accuracy while improving usability required continuous refinement.

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What I learned

This project completely changed how I think about software development.

As a physician without a traditional software engineering background, I discovered that modern AI can dramatically accelerate the creation of high-quality medical applications.

More importantly, I learned that combining clinical expertise with AI creates tools that can have real impact on healthcare education and clinical practice.

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Future plans

PulmoCalc is only the beginning.

Future development will include:

• AI clinical assistants
• Personalized learning pathways
• Intelligent workflow automation
• Expanded evidence-based pulmonary guidelines
• Multilingual support
• Additional medical specialties

My long-term vision is to build an AI-powered ecosystem that helps physicians learn faster, make safer decisions, and spend more time focusing on patient care.

Thank you, OpenAI, for creating the tools that made this project possible.

Built With

• chatgpt-sites
• clinical-decision-support
• healthcare
• medical-ai
• medical-calculators
• prompt-engineering
• pulmonology
• web-application