Veronika Nemcova

I moved from the Czech Republic to Denmark when I was 18 to pursue both my Bachelor's and Master's degrees. Along the way, I developed a strong passion for research, user-centered design, and human-AI interaction.

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About Me

I am a 25-year-old UX/UI designer who is also skilled in front-end development. I have a strong passion for user-centred design, research and problem solving. Group projects at the university have not only taught me good research techniques and project management but also how to be a team leader and work as part of a group. For over three years I have been involved in the EU funded RES-Q+ project, which focuses on the improvement of post-stroke care worldwide through digital solutions such as conversational agents or natural language processing systems.

Education

Medialogy is a unique study that equips its students with skills from multiple fields of expertise. Programming, interface design, data analysis, cinematography and artificial intelligence are some of the various courses taken. Additionally, not only do students learn how to work and be part of a team, they also get an understanding of how to conduct research, design a project, implement a product, evaluate and analyze data. As part of the exam students are taught to present and reflect on their project, which is an important process for improving one's skills.

Revolutionizing Stroke Care with AI


I have been working with RES-Q+ for three years as part of this EU-funded Horizon project, aimed at transforming stroke care across Europe. RES-Q+ enhances the global REgistry of Stroke Care Quality (RES-Q) platform by integrating AI-powered natural language processing for automated data entry. This innovation improves healthcare efficiency, reduces costs, and saves lives. Additionally, we’re developing virtual assistants to enable seamless data use by patients and physicians, driving significant improvements in stroke care quality throughout the continent.

My work on the project included focusing on the Data Import Tool (DIT), the Patient Virtual Assistant (pVA), and the Clinician Virtual Assistant (cVA).


Patient Virtual Assistant (pVA)

The patient Virtual Assistant (pVA) project is designed to help patients answer medical questionnaires and address stroke-related questions. Utilizing AI technology, the PVA enhances patient engagement and provides timely support for managing stroke-related concerns.


WannaShare - App for sharing expences

I have designed a shared expenses app with my partner after we struggled to find one with good usability and design. Together, we are implementing and refining it to be simple, sleek, and easy to use—perfect for groups settling costs, like trips where everyone pays for something.


Streamlining Data Entry with the Data Import Tool (DIT)

The Data Import Tool (DIT) project is designed to enhance the efficiency of data entry into the RES-Q registry by automating the import of critical information from patient discharge letters through advanced natural language processing.


Clinician Virtual Assistant (cVA)

The clinician Virtual Assistant (cVA) aids healthcare professionals in analyzing care quality indicators and identifying trends. By generating visualizations from RES-Q data, the cVA helps clinicians understand changes in care quality and forecast future performance, ultimately improving patient outcomes.

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Streamlining Data Entry with the Data Import Tool (DIT)

Project Goal:

The Discharge Importer Tool (DIT) aims to streamline data entry for clinicians by automatically extracting relevant information from patient discharge reports using natural language processing (NLP). Its split-screen interface displays the discharge letter on the left and the input form on the right, allowing users to review and confirm the accuracy of pre-filled data fields.

My Contributions:

  1. Target Group Research: Gathered research on the target group, identifying user needs and creating scenarios to ensure the DIT aligns with clinician workflows.
  2. Prototype Testing: Tested the current prototype with clinicians to gather feedback on usability and functionality, informing necessary adjustments.
  3. Iterative Design: Iterated the design through wireframes, mockups, and UI designs, refining the user interface based on clinician feedback and usability testing.
  4. User Scenarios Development: Created user scenarios to illustrate the context of interactions with the DIT, ensuring that the tool meets the needs of diverse clinician personas and their workflows.
  5. Functional Requirements and NLP Prediction: Established detailed functional requirements to guide DIT development, including the design of NLP prediction presentations that minimize bias and enhance user trust in the system.

Outcome:

The outcome of this project is a comprehensive design document that outlines all aspects of the Discharge Importer Tool (DIT). This document includes user requirements, functional specifications, and design rationales, ensuring a clear understanding of the tool’s functionality and workflows. By providing detailed guidance on the implementation of the DIT, it aims to facilitate efficient development and integration into clinical settings.

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Patient Virtual Assistant (pVA)

Project Goal:

The goal of the patient Virtual Assistant (pVA) is to support stroke patients by helping them complete medical questionnaires and providing access to stroke-related information. It is designed to improve patient engagement by offering a straightforward way to manage their own health data. Ultimately, the pVA aims to streamline the collection of patient-reported outcome measures, contributing to better-informed stroke care.

My Contributions:

  1. User Needs Assessment: Conducted research to understand patient needs, focusing on accessibility and usability for stroke survivors.
  2. Personas and Scenario Development: Developed seven detailed personas and scenarios to guide the design of the pVA, ensuring it effectively addresses diverse patient needs and interaction styles.
  3. Prototype Development and Iteration: Created initial Figma prototypes and led Wizard of Oz workshops to simulate interactions, iteratively refining the design based on direct patient feedback and usability insights.
  4. Conversational Flow Framework: Established a framework for the VA's conversation flow, drawing on literature analysis to ensure natural and effective communication with patients.
  5. Functionality and Interface Design: Defined core features and interface elements specifically for stroke patients, focusing on usability and intuitive navigation.
  6. Requirements Documentation: Compiled comprehensive functional requirements and specifications, providing a clear development roadmap that aligns with patient needs and project objectives. I visualised the process of one of the requirements, which was linking the pVA to the RES-Q database. Below you can see the original mapping of the process and my redesigned version:
  7. Continuous Design Improvements: Integrated findings from usability studies and workshops into ongoing design iterations, ensuring the pVA remains user-centered and effective in real-world applications.

Outcome:

The outcome of the pVA project is a comprehensive service design document that outlines the final design and functionality requirements of the patient virtual assistant. This document serves as a crucial resource for developers, detailing user needs, interaction scenarios, and usability insights gathered from stroke survivors. By providing clear guidelines and specifications, it ensures that the pVA effectively meets the accessibility and usability needs of its intended users.

Additionally I designed an academic poster for one of the pVA user studies:

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Clinician Virtual Assistant (cVA)

Project Goal:

The goal of the clinician virtual assistant (cVA) is to enhance healthcare quality by providing clinicians with data-driven insights and visualizations that support informed decision-making. It aims to streamline the analysis of care quality indicators, enabling clinicians to identify trends, assess the impact of treatments, and benchmark against guidelines and peer institutions. By facilitating easy access to relevant data, the cVA empowers clinicians to improve patient outcomes and optimize care delivery.

My Contributions:

  1. Design and User Experience: Developed the overall design and user experience of the cVA, focusing on usability and efficiency for clinicians.
  2. Figma Prototyping: Created interactive Figma prototypes to visualize the cVA's interface and functionality, enabling iterative feedback and refinement.
  3. Frontend Implementation: Collaborated on the frontend implementation of the cVA, ensuring alignment with design specifications and enhancing user interaction.

Outcome:

The outcome of the clinician virtual assistant (cVA) project is a fully designed and user-tested tool that helps clinicians efficiently analyze care quality data through intuitive visualizations. The cVA supports informed decision-making by enabling easy access to trends and benchmarking insights, which ultimately aids in improving patient outcomes. With a clear design and detailed functionality requirements, the project provides a solid foundation for seamless development and implementation in clinical settings.

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WannaShare - App for sharing expences

Project Goal:

I have designed a shared expenses app with my partner after we struggled to find one with good usability and design. Together, we are implementing and refining it to be simple, sleek, and easy to use—perfect for groups settling costs, like trips where everyone pays for something.

Group Expense Screen:

  1. Search previous expenses: Identified the need for users to verify existing expenses and designed a search feature that supports quick lookup, helping prevent duplicates and improve clarity in the expense tracking flow.
  2. Overview of Total Expenses Amount: Recognized that the amount is the most critical piece of information for users when reviewing expenses. Designed the layout to ensure the amount remains visible at all times, reducing cognitive load and helping users stay oriented as they interact with the interface.
  3. Reminder System to Nudge Users: Observed that group members often forgot to settle their shared expenses. To address this, I introduced a user-friendly reminder feature that allows users to ping others who haven’t paid yet—making it easier to follow up without awkwardness and keeping payments on track.
  4. Clear Color Coding: To reduce ambiguity and improve at-a-glance understanding, I introduced a clear color-coded system indicating whether a user owes money or is set to receive it. This visual distinction helps users quickly grasp their status without needing to read through details.

New Expense Creation:

  1. Recent Expense Preview to Prevent Duplicates: To help users avoid accidentally adding the same expense twice, I designed a feature that surfaces the most recent expense with the same name as you're typing. This gives immediate context and reduces the chance of duplicates being created.
  2. One-Tap Shortcut for Even Splits: Recognizing that evenly splitting expenses is the most common use case, I added a quick-access shortcut to simplify the process. This reduces friction and speeds up the flow, letting users divide costs with a single tap.
  3. Flexible Custom Splits for Uneven Expenses: To support more complex scenarios like splitting by percentage or covering specific shares, I designed a custom split option. This feature gives users full control over how expenses are divided, ensuring fairness and adaptability for any situation.
  4. Clear Payout Flow: Who Pays and Who Gets Paid: To avoid confusion during settlements, I focused on making it easy to distinguish between payers and receivers.
  5. Tagging System for Smarter Organization and Insights: Introduced a tagging feature that lets users categorize expenses—making it easier to search by type or context. Beyond organization, this also lays the groundwork for future data visualizations, like tracking spending trends across categories or months.

Quick Overview:

  1. Expense Overview for Clear Group Balances: Designed an overview screen that summarizes who owes what within the group. This high-level view helps users quickly understand outstanding balances, reducing confusion and making it easier to settle up.