Designing a cutting-edge ultrasound solution that detects blood clots within minutes.

Project type

Android & web app


Jul 21 – Feb 22


Founding product designer




Transforming how blood clots are detected

AutoDVT is an ultrasound solution that uses artificial intelligence to guide non-ultrasound medical professionals, such as nurses and GPs, in performing a deep vein thrombosis (DVT) ultrasound exam to detect blood clots. The tech dramatically reduces the cost and time to diagnose patients by increasing the number of medical staff who can perform the exam, not just radiologists. Multiple groups benefit from AutoDVT, including:

The seamless UX and AI enable Nurses and GPs to perform a DVT exam to detect DVT in minutes without formal ultrasound training.
Secondary Users
By assigning DVT exams to nurses and GPs in emergency rooms and other medical settings, radiologists can free up time to treat other health conditions that require their expertise, thus addressing the radiologist shortage.
Hospital directors  find AutoDVT valuable because it is an efficient and cost-effective diagnostic solution that will reduce operational costs.
Suspected DVT patients will receive a faster diagnosis and eliminate the need for medications and other tests at a more affordable cost.

Designing a beta release for clinical trials

I was the first designer at ThinkSono, a MedTech startup that develops intelligent ultrasound software. My role was to establish the user experience for AutoDVT right from the beginning. We aimed to release a beta version for clinical trials, gather clinical data, and prove that our product can detect DVT with better efficiency, speed, and accuracy while reducing cost.

ThinkSono, a MedTech startup that makes smart ultrasound software, began with a focus on funding, training, and perfecting their machine learning algorithm, the company's secret sauce. Then, with enough traction and success, ThinkSono was ready to move into product development. I was tasked to design the company's first product, AutoDVT.


This project was successfully designed and developed on time despite an ambitious deadline. We achieved a significant milestone by completing the core flows to release a beta version for clinical trials and collect data for FDA medical clearance. So far, the software has been deployed in 7 hospitals across Europe.

faster diagnosis

Wearing many hats as founding designer

As the founding designer, I led all UX efforts, including product strategy, interaction design, usability testing, and design handoff. Additionally, I successfully designed, launched, and managed the company's marketing website and several video projects.

Memo is a superb UX and UI designer. He gains a sound understanding of the product and business goals and scope, asks the right and critical questions and requires little to no guidance to come up with a fitting solution for any given problem..."

Read More

Sven Mischkewitz

Co-founder, thinksonO

What is DVT

The leading cause of preventable hospital deaths in the US

Deep vein thrombosis (DVT) is a blood clot that forms in the deep veins of the legs. If parts of the clot break off, it could travel to the lungs and cause a potentially deadly disease called pulmonary embolism (PE).


Patients are affected


People die


Cost to treat DVT

Annual U.S. stats | Source:

The problem

Inefficiencies with the existing diagnostic pathway

Compression ultrasound has proven to be an accurate and non-invasive modality for recognizing DVT. During the exam, a radiologist will apply pressure to the veins in the affected area using an ultrasound scanner. If the vein cannot compress, it indicates a blood clot.

However, a worldwide shortage of radiologists limits healthcare systems from diagnosing and treating DVT efficiently. As a result, patients often wait hours for test results due to the limited capacity of radiologists, making the treatment expensive, time-consuming, and only sometimes possible.

The solution

Empowering non-experts with AI guidance to scan key anatomy

Today, exams are done exclusively by radiologists or medical staff with extensive training limiting the number of individuals who can perform the exam. AutoDVT's frictionless AI guidance empowers non-experts by highlighting the veins of interest and providing step-by-step instructions to capture the correct data in the proper sequence, increasing the supply of staff who can perform the exam.

Here's how it works.

01 Finding the veins

With AI-powered written instructions, chimes, overlays, and other feedback, the app guides the user to correctly position and move the probe to find the vessels of interest.

02 Recording the compression

After finding the vessels, a 10-second recording of the vessels' compression is captured to be sent to the radiologist for a final diagnosis.

If the veins compress fully, it indicates no DVT.

03 Reviewing the scan recording

After recording the compression, the user reviews the clip and records whether the veins are compressed for a provisional assessment.

04 Radiologist's diagnosis

The provisional diagnosis is sent to the cloud dashboard for review, where a radiologist can log in remotely and make a final diagnosis.

Simplifying the number of steps and reducing the cost to get a DVT diagnosis.

≈ 5 min

Scans done by any doctor or nurse

Blood test not required

Low cost (≈$70) per scan

≈ 6 - 24 hrs

Scans only done by a specialist

Blood test required

High cost (≈$200) per scan


Opening up the design process

The UX process for this project had 5 key phases that focused on cross-functional collaboration and emphasized shared understanding so that everyone on the team had the same mental model of the problem space.

UX FLOwchart
Validating the flow and concept early

I mapped out a UX flowchart to validate the flow and concept early with minimum time invested; it was important for deliverables to be lightweight with a high impact.

The UX flowchart allowed us to get a quick collective overview of the entire process and allowed us to scope and prioritize the project. After a few iterations, we all agreed on the features the beta release would support and moved forward to design and implement our plan.

Designing the core experience first

With a solid understanding and team consensus on project scope and flow, I explored different scanning screen concepts before mocking the rest of the experience. I focused on the scanning screen because it is the app's core experience, and the rest of the content and navigation could be designed around it.

v4 chosen solution
Mid-fidelity scanning screen exploration
Refining the core screens

After exploring scanning screen concepts, it became evident that filling all the functionality we contemplated into a single screen was challenging and likely to decrease the learnability of the app. Therefore, I split the content into two screens to make the tasks easier to accomplish and scanning more straightforward.

Final exam PROT screen
Final scan screen
A holistic visual representation of the user flow

With ironed-out key screens, I mapped out a mid-fidelity wireflow to document the entire experience by combining wireframes and flowcharts to show complete views, paths, and interactions between screens.

Wireflows allowed us to have a common understanding of the product structure, supported me in gathering stakeholder feedback, and facilitated design discussions. As a result, Wireflows became an essential living document and were heavily referenced by the engineering team during implementation.

User Testing
Evaluating the design at the different stages

I tested at different stages of the design process. For example, I sometimes tested early to validate or invalidate assumptions before spending engineering time and resources. Still, at other times I would test before a release roll-out to see if specific elements or flows needed improvements. The approach was a mixed bag. It ranged from guerrilla-style testing to more formal in-person testing with relevant participants in the medical space.

We also observed real users interact with the actual product and gather key qualitative insights during clinical trial training sessions with nurses.

Testing session with a medical professional
Usability issues and improvements


Confusing CTA label

Users found the 'Star compression' button confusing because the actual vein compression happens outside the app by applying pressure using the ultrasound probe. The action button triggers a ten-second recording of the ultrasound image, so 'Record compression' was more in tune with the action.

Before scanning screen
After scanning screen with new CTA label


Inability to cancel a recording right away

After starting a compression recording, the app didn't offer a way to cancel it, forcing the user to wait and advance to the end of the flow before a retry option became available. Through user testing with novice users still getting familiar with the scan protocol, we noticed many of them showed signs of frustration.

I used the same record compression button that switched to a cancel action right after a compression recording had started.

Before scanning screen
After scanning screen with Cancel recording option


Ultrasound gel and latex gloves made interacting with the phone difficult.

During nurse training sessions, we learned latex gloves and ultrasound gel made tapping on interactive elements difficult, so we harnessed the probe's hardware buttons to make it easier for users to interact with the app. First-time users see an educational modal introducing the feature.

Modal with educational message
How we used it

Hardware buttons made it easier and faster for users to interact with the UI. For example, it became highly convenient when scanning, as even slight body movements when tapping the screen and taking the eyes of the scanner made users more prone to mistakes. It was also utilized on other screens throughout the app, such as the exam protocol screen shown below.

Scanning screen
Exam protocol screen
Design Library & handoff
Creating a visual language

I created a design library to organize UI components into a single source of truth file to achieve uniformity, speed, and a smoother design handoff. It includes logos, a color palette, 70+ UI components, icons, surfaces, typography, and stroke styles.

Benefit 1
Benefit 2
Benefit 3
Email confirmation
Log in
Start new exam
Patient details
Exam protocol
Before compression
Compression recording
Review compression
Save and exit

Delivered design on time despite tight deadline

The project's biggest constraint was time due to commitments with hospitals to begin clinical trials. However, I successfully managed to design, test, and deliver the final product on time.

AutoDVT in 11 hospitals across Europe

AutoDVT is already live in 7 hospitals in the UK and is in discussions to be implemented in further hospitals across Europe, Canada, and the United States.

Favorable preliminary results

Preliminary results indicate AutoDVT to be 30x faster than the existing clinical pathway without sacrificing accuracy.

Established a relationship with ThinkSono

Through my work and collaboration, I gained the team's trust, which led to additional work, such as researching the feasibility of future applications, designing the company's marketing website, and designing the reviewer's Android mobile app.

Watch AutoDVT in action
Watch Autodvt in Action.
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