Mobile / Healthcare

AI Health Assistant

An intelligent module that helps patients understand their symptoms before visiting a clinic, through visualizations and AI-guided questions.

MobileHealthcareAI

Timeline: ~2 weeks
My Role: End-to-end design: UX flows, UI design, prototyping
Team: Solo
Tools: Figma · Miro

Overview

The AI Health Assistant is an intelligent module that helps patients better understand their symptoms before visiting a clinic. It asks users about their symptoms through visualizations and questions, provides tailored tips and guidance using AI, and supports patient awareness and preparation before consultations. Works independently or as a module within IQLINIQ.

Problem Space

Patients often arrive at a clinic unsure how to describe what they're feeling. Generic symptom checkers feel clinical and raise anxiety instead of easing it. Key problems:

Patients often feel uncertain about their symptoms before visiting a clinic
Many don't know how to track or interpret symptoms effectively
Without preparation, patients arrive unsure how to describe what they're feeling, which slows the consultation

Key Observation Insights

My research surfaced:

In existing tools, symptom input was almost always text-heavy and clinical, assuming users already knew the medical words
Very few tools used a conversational or visual approach, even though that's what actually lowers health anxiety
Most were vague about whether they offered guidance or a diagnosis, and that ambiguity was where user trust broke down

Key Research Insights

Tone and visual design are critical for reducing health anxiety
Step-by-step AI questioning makes symptom gathering feel natural
Clear communication about the AI's role reduces confusion and builds trust

Challenges & Solutions

Challenge

Ensuring clarity that the tool is for guidance, not treatment.

Solution

Clear communication, appropriate disclaimers, and visual design that feels supportive rather than clinical.

Challenge

Designing adaptive question flows that feel intuitive and natural.

Solution

Multiple prototypes and feedback loops with clinicians and patients ensured usability and trustworthiness.

Outcomes

Helped patients better understand and track their symptoms
Increased patient engagement and preparedness for clinical visits
Seamlessly integrated into IQLINIQ while maintaining standalone flexibility

Future Improvements

Enhanced personalization of tips based on symptom patterns
Integration with wearable health data
Multi-language support for broader accessibility