How blockchain assists the improvement of healthcare?

Maciej Zieliński

13 Apr 2023
How blockchain assists the improvement of healthcare?

Introduction

When you will find yourself in a hospital, the method at which your data is processed is the last thing you will be probably thinking about. However, it may be the key to your successful recovery. Why would the form of storing the data be so important and why does the blockchain seem to be the most optimal solution in this case? In this article we will dive into the topic of blockchain and healthcare, explain why is it important as well as show a real use case.

Why blockchain and healthcare?

The medical sciences are based on sheer facts and is fully dependent on them because their validity is a difference between the life and death of patients. The new medicine brought to the pharmacies, newly researched healing method or the project of a new tool wouldn’t be possible without a thorough analysis of hundreds of terabytes of data. We probably do not have to explain why is an accurate analysis of patients health and the information processed by the healthcare so necessary. The need to create and maintain massive databases with reliable and accessible information appears to maintain the proper flow of information between the experts and hospitals.

The key features of the usage of blockchain is the ability to protect the reliability of the data stored in its systems and to ease the flow of information between its systems. Thanks to that we reduce the human error margin and the risk of the loss or theft of data. This is why blockchain can prove to be revolutionary when it comes to aggregating data in the healthcare.

Blockchain in the medical e-documentation

In the last decades the need for the digitalization of medical documentation has increased significantly and has been requested by both doctors and patients around the world. Such a way of storage of data about the patients’ health, his medical referrals or the results of his testing makes them more accessible and eases the procedures that use them. After all the patient confronts many types of specialists on his road to health so any situation where  the medical history is inaccessible seems absurd.

Perhaps the main disadvantage of modern registries is the fact that they are scattered in between many facilities. The patients very often are forced to use many different medical services because of their life situations. Because of that, the data about their previous treatments is often lost or inaccessible. In Poland for example, many patients use both the private and the national healthcare which makes it difficult to control which of the EDM (electronic medical documentation system) systems would be used to allow the information to flow and so some doctors have difficulties with accessibility of data from his peers. Because the private medical facilities decide which EDM system they shall use independently, the communication between the different systems is usually lost. This translates into the lowered quality of decisions undertaken in reference to treatment and makes it difficult for the patient to access the documentation. Additionally when EDM is applied the data is often threatened by the audit, provenience and the loss of control.

Blockchain as a Solution

Solutions based on blockchain could potentially become a base for answering those issues. For example, MedRec system, tested by the Beth Israel Deaconess Medical Center uses the advantages shown by the blockchain to provide the users with confidentiality, integrity and an ability to easily verify data. Such a decentralised system of data gives its users an unchangeable medical documentation and allows for ease in accessing it in many situations.

An important trait of MedRec is the ability to let the patient be responsible for his own data. The system only holds a hash of the record of the medical documentation and informs the patient where the record should be held at. The hash allows for the record to be unchangeable and the users interface makes it sure that the medical documentation is consistent in between the medical facilities. This allows the record to be available for both the private and the national medical institutions as it is stored independently from them and is not limited to either.

A common trait between the blockchain based solutions like MedRec is the ability to exchange the medical data while there is a simultaneous confidentiality of the personal data. The first country which has discovered the potential behind this technology seems to be Estonia, where there was a first proposition of using the blockchain to maintain the EDM system.

Where shall we use the blockchain in the future?

In recent years, neurology of technological solutions had its fair deal of advancements. It has excited people around the world and left them hungering for more.  Its no surprise since the modern times strive towards less and less mechanical interaction with the infrastructure and the ability to control the facilities with the power of our own mind. Such neurological devices can interpret the patterns of brains activity and translate them into actual commands towards the external devices and interpret the psychological status of a person. However, in order to make such solutions work  we would need to digitalise the brain. Once again, blockchain can prove to become an indispensable tool to assist us in achieving that.

One of suggestions for such an implementation is storing the “thought files”, which would work like the compound elements of data of chains of personal thoughts which can be shared inside of a peer-to-peer system. This kind of blockchain thinking is proposed as a calculation system of processing the entering data with several functions that give the AI chance to integrate with the human brain.

Multicomponent verification which connects to the personal chain of thoughts as a blockchain implementation  can allow a safe cryptography of creation of joint numerical data for people. Such joint data reduce the number of silos of human data which also allows every human to keep their own private property and to share their own experience.  

Blockchain in Healthcare Use Case: Neurogress

One of the companies that confirmed their desire to use the blockchain technology to store the human brain activity data is Neurogress. Registered in Geneva and created in 2017, this company is keen on construction of neural control systems which will allow all of its users to control the machines, drones or AR/VR devices through the power of their mind. The Neuroregress system is focused on the usage of machine learning that is used in order to improve the ability to read the brains activity. Huge amounts of data about the neural activity is required to train the AI to use the system. The company defines the data with the usage of exabytes (1 exabyte = 1 billion gigabytes). Its no wonder the Neurogress will use blockchain as it allows the safety and privacy for data in large quantities.

Thanks to the ability to register the data of the user in decentralised blocks of chains is immune to manipulations and breaches. The system will allow the safety and confidentiality to its users because most of the suspicious activities are easily detectible. Simultaneously the usage of blockchain allows the Neurogress system to be open and accessible to its users.

Blockchain healthcare – the future of medical databases

The constant growth of medical sciences will bring much more data to process in the future. Quick processing of exchange between the facilities can become key in the improvement of the treatment process. Solutions which bring such a need will reduce the cost of procedures and the time needed to carry them out, they will reduce the usage of resources which are increasingly scarce. Additionally, the growing social awareness concerning the data and its protection will increase the need for the application of blockchain in the medical sector. As it offers an innovative look into the storage of data which assures its safety, reliability and quick exchange on the protocol level, it can become a solution that will let us both improve the existing methods and create newer, better ones.

Conclusion

To summarize, blockchain healthcare has the potential to transform the way patient data is stored and managed. Employing a secure, dependable, and decentralized approach for data aggregation, blockchain technology not only ensures patient privacy but also streamlines the exchange of information among hospitals and medical professionals. The MedRec system exemplifies this by empowering patients to control their data while preserving its confidentiality and consistency across various healthcare facilities. Moreover, applying blockchain technology to digitize brain data for neurological devices is another promising avenue being pursued by companies like Neurogress. In essence, blockchain healthcare offers promising solutions for data management and privacy concerns within the industry.

Want to know more about using the emerging technologies in medicine? Check out our article on AI in medice.

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series