1. Smart Symptom Collection
Patients enter primary symptoms via intuitive forms.
HeAIth was born from using AI to diagnose a skin condition, avoiding months of NHS waiting or £200+ private dermatology fees.
I had a persistent skin condition but couldn't get timely NHS dermatology. Wait times were months, private fees prohibitive. As a software engineer researching AI, I turned my focus to diagnostics, I research lots about diagnostic workflows and then I constructed a diagnostic flow that successfully found the likely cause.
It worked. The condition cleared completely, saving time and money.
This realisation followed: this process could become a powerful diagnostic system democratising healthcare worldwide. NHS doctors work under immense strain while patients with straightforward conditions wait months.
That is HeAIth today: clinical decision support tools helping NHS clinicians see more patients efficiently, provide faster reassurance where appropriate, and ensure urgent cases get care sooner. Supporting doctors, not replacing them.
MediScreenAI brings this vision to life. I am a software engineer, not a clinician. Which limits my ability to test the accuracy, improve the accuracy and ensure it is a product that doctors and patients will use. That is why I am assembling a Clinical Advisory Board of practicing GPs to guide MediScreenAI development.