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Client  I   NeuralMed

Role  I   Freelance Product Designer

Services I   Research, UX/UI 

NeuralMed is a Healthcare startup developing AI-based solutions to optimize the screening flow and diagnosis of patients in the hospital ecosystem. I teamed up with their group of data scientists to redesign Florence, a platform for medical image annotations.

THE ORIGINAL ONLINE STORE

THE UNSUNG HEROS 

OF AI DEVELOPMENT

The task of annotating medical data for healthcare algorithms is a time-consuming and tedious work without any of the flare associated with sci-fi-like thinking.
 

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THE CHALLENGE

NeuralMed’s team needed millions of verified results to train their machine. So, they decided to improve the interactive experience of Florence for the doctors who do this work.

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Video of the old platform

DISCOVERY PHASE

Early on in the process, I conducted interviews with several radiologists and summarized

key findings that characterized who they are and their annotating experience.

THE USERS

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Brazilian Radiologists who
specialize in XR and CT scans

Over 10 years of experience working 

in hospitals and private clinics

Dedicating 8-10 hours a week to
annotate images for extra income

Motivated to label X amount of images each week to reach a set financial goal

THE EXPERIENCE

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Repetitive Process - Skilled radiologists can label images within several seconds

Lack of Feedback - Annotators are not valued for being quick or accurate

Monotonous Work - Lists of datasets force the same type of annotation

Wrong Motivation - To speed the process doctors often add less labels

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VISION AND

STRATEGY

Our goal was to create additional value for users by adding tools that encourage personal growth and involvement - such as progress bars, leaderboards and customized dataset opportunities.

IMPROVING FLORENCE

UX DESIGN PROCESS

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OLD MENU SCREEN

  • Featured only Xray data ('Raio-X)

  • Allowed doctors to select between labeling images of children or adults ('Indantil / massa')

  • Featured earnings in a different window ('Checar atividade') 

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NEW MENU SCREEN

  • Features a selection of 'bundled' images including CT scans and NLP reports

  • Each set bundle has a set prize tag

  • Clear depiction of monthly earnings and relevant annotating stats

  • Illustrates the doctors 'ranking' in relation to the community  

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OLD LABELING PROCESS

  • Medical prognosis in text form with no 'free annotation' labels (like 'other')

  • Label annotation tool unclear (frames box tool, drawing shape etc)

  • Menu of view options also in textual format 

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NEW LABELING PROCESS

  • Medical prognosis menu presented clearly with relevant iconography

  • Progress bar showing completion rate

  • View menu presented using icons

  • Set prize and earnings featured on screen at all times

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POSITIVE FEEDBACK

  • Upon set completion doctors receive feedback with new account balance

PROTOTYPING & VALIDATION

USABILITY TESTING

We built a lean version of the platform and tested our ideas with several doctors to evaluate their response and collect feedback.

Usability Testing with Dr. Alexandre Penteado

Usability Testing with Dr. Alexandre Bialowas

THINGS WE FIXED

FEEDBACK IMPLEMENTATION 

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LEADERBOARD
FEATURE

During the testing we discovered that the financial leaderboard is making doctors feel uneasy, since speaking of 'earnings' is considered taboo in Brazil. So, we decided to change the ranking system to feature only XP points.

CALL TO ACTION

In the main menu, some doctors said that our original 'PLAY NOW FOR' button feels as though it is something they need to pay for.

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LABELING OPTIONS

Following the feedback of doctors we also decided to give doctors the option to add labels which are not predefined ('Other').

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