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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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

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!