Oct. - Dec. 2022


UI/UX Design, Ecosystem Design, Animation


Figma, Adobe Illustrator, Adobe After Effects



Inspired by my grandfather's experience with a chronic illness, I collaborated with medical experts to design an AI and Machine Learning-based app. This innovative solution focuses on early detection and intervention for chronic diseases, fostering a proactive approach to healthcare and enhancing well-being.

Product Video

Explanation Video


Chronic illnesses often have complex symptoms that may not be easily diagnosed, leading to delayed treatment and negative health outcomes. Patients with chronic illnesses may need to make significant lifestyle changes, such as adopting a healthier diet or increasing physical activity, in order to manage their condition. These illnesses account for 70% of deaths in the United States and are responsible for the loss of over 1.7 million American lives each year.

In the healthcare field, artificial intelligence and machine learning algorithms are being utilized to identify patterns in medical images and patient data, allowing for more accurate predictions about the presence or likelihood of specific conditions or diseases.

How Might We use the Power of Artificial Intelligence, to let more people Detect and Avoid Disease at an Early Stage?

Initial Brainstorm

Through extensive secondary research, I gained valuable insights into the advancements of artificial intelligence in healthcare. I thoroughly analyzed the pros and cons of existing AI solutions that have the potential to revolutionize the healthcare industry. This research allowed me to gain a deeper understanding of the challenges and opportunities that exist in the field of AI in healthcare and helped me develop an innovative solution focused on early detection and intervention for chronic diseases.

Primary Research

To better understand the pain points of users throughout the entire consultation process, I conducted primary research by dividing the user experience into three parts: before, during, and after hospital. I developed three main questions to guide my research and gathered insightful results. By analyzing the data, I was able to identify the specific pain points that users face at each stage of the consultation process. This allowed me to design an AI and machine learning-based app that addresses these pain points and fosters a more proactive approach to healthcare.

Have you ever had a symptom that you didn't know how to deal with, and then it later became severe?

Do you understand your test reports every time?

Have you ever forgotten to take medication or other things that needed attention back to home from hospital?


I conducted in-depth interviews with four individuals experienced in the disease and a medical student, gaining valuable insights into patients' specific challenges and pain points when dealing with medical issues. These insights informed the design of the AI and machine learning-based app.


To understand potential users' needs and pain points, I developed personas based on primary research data. Each persona represents a target user with unique characteristics, needs, and pain points. This approach allowed me to design the app's functionality to cater to a broad range of individuals.

Competitor Analysis

I conducted a thorough competitor analysis to understand the healthcare app market's competition. This involved researching and comparing the features, functionality, and user experience of several healthcare apps.

User Journey

By identifying pain points at each stage, the app was developed to offer personalized guidance, reminders, and resources to help users navigate the healthcare system more easily. Whether it's providing users with educational resources before their consultation, offering appointment reminders, or tracking medication schedules, the app is designed to enhance the overall patient experience and promote proactive healthcare management.

Mid Fidelity - Mobile

I designed mid-fidelity prototypes that allowed me to test the app's functionality and user experience. These prototypes included interactive wireframes and clickable designs that simulated the app's interface and functionality. This allowed me to conduct usability testing, identify potential issues, and make necessary adjustments before moving onto the high-fidelity design stage.

Mid Fidelity - Watch

Final Design

After multiple iterations, I transformed the UI from mid-fidelity to high-fidelity, focusing on creating a design that is both reliable and memorable.

1. AI Online Consultation

Chat with our AI robot, Fettle, to learn more about your symptoms and possible diseases.

Quickly make an appointment with a nearby hospital to receive the care you need.

Read Articles

Read articles written by experts to learn basic information about your disease, including:

1. a brief introduction
2. possible causes
3. the symptoms.

History Suggestion

Get a clear understanding of the detailed information

Quickly access the suggestions provided by Fettle in your history.

Report Analysis

The AI system will analyze the reports uploaded by the hospital, providing feedback and advice on how to improve your health conditions.

The doctors will review the AI's analysis of the report, and if there are any errors, the doctor will withdraw the analysis.

Check History Reports

To view the history of check tests, click to see all the information for that specific test.

Risk Warning

Once the results of your report are available, the doctor will upload them into the system, and Fettle will analyze all potential risks, notifying you of any possible future diseases.

Every step of the process involves physician intervention.

Daily Goals & Reminders

Check upcoming events and view further information

Keep daily goals in mind to prioritize important tasks.

Daily Goals Notifications

Receive reminders if yesterday's goals were not completed

Be notified when a certain period of treatment has been completed.


Receive notifications when your medical report is updated or when there is a problem with your medical condition.