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Technology Trends in 2023

In the past couple of years, we have witnessed revolutionary breakthroughs in technology. In a post-pandemic world, anything is possible. Technology will continue to influence how we live and work in 2023. As more products and services include artificial intelligence (AI) and machine learning (ML), they become smarter and more capable of carrying out jobs that were previously solely performed by humans. 

Here are some trends that will shape 2023:

  1. Web3/Blockchain: The blockchain ledger is being utilized in various contexts, including the protection of patient data, accelerating transaction times, reducing digital fraud, and more. By 2030, according to a report by Statista, the market is projected to grow by a CAGR of 82.8% touching $1,235.71 billion. 
  • Asset Tokenization: It is anticipated that some sectors, like healthcare and finance, may choose private blockchains in the years to come due to the requirement for greater security and privacy. The BFSI, retail, travel & hospitality, healthcare, IT & telecom, and media & entertainment are the different market segments for tokenization. The BFSI industry is anticipated to hold the most significant market share for tokenization in 2023. The expansion of this market is attributed to the rise in payment security solutions adoption and data breaches in the BFSI industry.
  1. Web AR: Some benefits of using Augmented Reality in business are boosting sales, minimizing returns, increasing customer engagement, collecting data on customer preferences, and providing a contactless experience. Users can now virtually try clothes and jewelry before purchasing on websites like Candere and Hazoorilal with the help of Web AR. Beauty and wellness platforms like Nykaa and Purplle let one try on lipstick shades digitally before purchasing them. Leading eCommerce portal for eyewear Lenskart allows customers to try on different frames virtually to choose the right one. Web AR is also used in education, taking the learning process to another level. It can be used to understand complex study models. For eg: Medical students can study human anatomy and even train for surgery on it.

Luminaire, a German-based aggregator of in-home and office lighting solutions partnered with Mantra Labs to create an AR model through paper catalogs, hand sketches, technical/2D drawings, and an interactive product database for products with electrical, luminous, & mechanical specifications.

  1. Adaptive AI: Unlike conventional AI systems, adaptive AI can modify its own learning strategies to account for changes in the actual world that weren’t anticipated when the system was created. By 2026, Gartner predicts that businesses that have implemented AI engineering methods to create and oversee adaptive AI systems will outperform their rivals in terms of the quantity and speed of operationalizing AI models. 

Hitee, Mantra Labs’ industry-specific AI-driven conversational chatbot helps insurance enterprises with customer onboarding by creating workflow automation, ticket queuing, etc.

  1. Metaverse: According to Forbes, the metaverse will contribute $5 trillion to the world economy by 2030, and 2023 will be the year that determines the metaverse’s course for the following ten years. Further, it says that by 2023, we’ll have more immersive meeting spaces where people can collaborate, develop, and create things. 
  • Education and learning: Mesh is a mixed reality collaboration and communication platform by Microsoft for staff, faculty, and students to interact using 3D avatars. 
  • Banking and finance: Metaverse in banking is reaching new heights. From any place, the banking metaverse provides a 360-degree picture of actual banks. One can still use their laptop or mobile device to access Metaverse banking even if they don’t own a VR headset.
  • Healthcare: Patients and doctors can communicate in virtual 3D clinics under the umbrella of telemedicine and telehealth, a notion made popular by the Metaverse after the pandemic. Another example is the Metaverse-powered Digital Twin technology, which enables the creation of a patient’s digital representation for the purpose of testing therapies and medications.
  1. Predictive analytics in Logistics: Playing a significant role in logistics by enabling businesses to foresee demand, anticipated delivery dates, and optimize the supply chain, the predictive analysis will result in quicker deliveries, less waste, and cheaper prices.

Hwy Haul, a California-based freight brokerage startup, partnered with Mantra Labs to create a portal to track their freight from booking to end a carrier portal to manage their fleet and drivers, an OPS portal to manage operations and backend systems, and a driver mobile app to deliver conveniently.

Key takeaways:

Technology has always been evident in every ecosystem. However, with the advent of AI and data analytics, one can expect a rather structured, sustainable, and creative take on things. While existing technologies continue to serve and enhance the customer experience, one will witness new ideas and experiments to promote a convenient and conscious lifestyle.

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Conversational UI in Healthcare: Enhancing Patient Interaction with Chatbots

As healthcare becomes more patient-centric, the demand for efficient and personalized care continues to grow. One of the key technologies that have gained traction in this domain is Conversational UI (CUI) — a user interface where interactions occur through natural language, often with the help of chatbots. For developers, building a robust CUI in healthcare requires a balance of technical proficiency, understanding of the healthcare landscape, and empathy toward patient needs. Let’s explore how CUI can improve patient interactions through chatbots and what developers should consider during implementation.

Why Conversational UI is Gaining Popularity in Healthcare

From scheduling appointments to answering medical queries, healthcare chatbots have become vital tools for enhancing patient engagement and streamlining healthcare workflows. Conversational UIs enable these chatbots to interact with patients naturally, making them accessible even to non-tech-savvy users. By incorporating AI and NLP (Natural Language Processing), chatbots can now simulate human-like conversations, ensuring patients receive timely, relevant responses. 

Image credit: https://www.analytixlabs.co.in/blog/ai-chatbots-in-healthcare/ 

Key Areas Where Chatbots Are Revolutionizing Healthcare

  1. Appointment Scheduling and Reminders – Chatbots can automatically schedule appointments based on patient availability and send reminders before the visit, reducing no-show rates. For developers, this feature requires integration with hospital management systems (HMS) and calendar APIs. The challenge lies in ensuring secure and real-time data transfer while adhering to healthcare compliance standards like HIPAA.
  1. Medical Query Resolution– Chatbots equipped with NLP can answer common patient questions related to symptoms, medications, and treatment plans. This reduces the burden on healthcare providers, allowing them to focus on more critical tasks. Developers working on this feature need to consider integrating medical databases, such as SNOMED CT or ICD-10, for accurate and up-to-date information.
  1. Patient Monitoring and Follow-ups – Post-discharge, chatbots can monitor a patient’s condition by regularly asking for health updates (e.g., vital signs or medication adherence). Developers can integrate IoT devices, such as wearable health monitors, with chatbot platforms to collect real-time data, providing healthcare professionals with actionable insights.
  1. Mental Health Support – Chatbots have shown promise in offering mental health support by providing patients with an outlet to discuss their feelings and receive advice. Building these chatbots involves training them on therapeutic conversational frameworks like Cognitive Behavioral Therapy (CBT), ensuring they offer relevant advice while recognizing when a human intervention is required.

Key Considerations for Developers

1. Natural Language Processing (NLP) and AI Training

NLP plays a pivotal role in enabling chatbots to understand and process patient queries effectively. Developers must focus on the following:

Training Data: Start by gathering extensive datasets that include real-life medical queries and patient conversations. This ensures that the chatbot can recognize various intents and respond appropriately.

Multi-language Support: Healthcare is global, so building multi-lingual capabilities is critical. Using tools like Google’s BERT or Microsoft’s Turing-NLG models can help chatbots understand context in different languages.

Contextual Understanding: The chatbot must not just respond to individual queries but also maintain the context across the conversation. Developers can use contextual models that preserve the state of the conversation, ensuring personalized patient interactions.

2. Security and Compliance

Healthcare chatbots handle sensitive patient information, making security a top priority. Developers must ensure compliance with regulations such as HIPAA (Health Insurance Portability and Accountability Act) in the U.S. and GDPR (General Data Protection Regulation) in Europe. Key practices include:

  • Data Encryption: All communication between the chatbot and the server must be encrypted using protocols like TLS (Transport Layer Security).
  • Authentication Mechanisms: Implement two-factor authentication (2FA) to verify patient identity, especially for sensitive tasks like accessing medical records.
  • Anonymization: To avoid accidental data breaches, ensure that the chatbot anonymizes data where possible.

3. Seamless Integration with EHR Systems

For chatbots to be truly effective in healthcare, they must integrate seamlessly with Electronic Health Record (EHR) systems. This requires a deep understanding of healthcare APIs like FHIR (Fast Healthcare Interoperability Resources) or HL7. Developers should aim to:

  • Enable Real-time Updates: Ensure that chatbot interactions (e.g., new appointment schedules, and symptom checks) are instantly reflected in the patient’s EHR.
  • Avoid Data Silos: Ensure that all systems (EHR, chatbot, scheduling system) can communicate with each other, eliminating data silos that can lead to fragmented patient information.

4. Scalability and Performance Optimization

In healthcare, downtime can be critical. Developers need to ensure that chatbots are scalable and capable of handling thousands of patient interactions simultaneously. Using cloud-based platforms (AWS, Google Cloud) that offer auto-scaling capabilities can help. Additionally, performance optimization can be achieved by:

  • Caching Responses: Store frequently used responses (such as FAQs) in memory to speed up interaction times.
  • Load Balancing: Implement load balancers to distribute incoming queries across servers, ensuring no single server is overwhelmed.

Tools and Platforms for Building Healthcare Chatbots

Several tools and platforms can aid developers in building healthcare chatbots with conversational UIs:

  1. Dialogflow (Google): Offers pre-built healthcare intents and integrates with Google Cloud’s healthcare APIs.
  2. Microsoft Bot Framework: A scalable platform that integrates with Azure services and offers AI-driven insights.
  3. Rasa: An open-source NLP tool that provides flexibility in creating highly customized healthcare bots.

Conclusion

Conversational UI in healthcare is transforming patient care by offering real-time, scalable, and personalized interactions through chatbots. However, for developers, building these systems goes beyond programming chatbots — it involves understanding the unique challenges of healthcare, from regulatory compliance to seamless integration with hospital systems. By focusing on NLP capabilities, ensuring security and privacy, and integrating with existing healthcare infrastructure, developers can create chatbots that not only enhance patient interaction but also alleviate the burden on healthcare providers.

References

  1. NLP in Healthcare: Opportunities and Challenges
  2. HIPAA Compliance for Chatbots

About the Author:

Shristi is a creative professional with a passion for visual storytelling. She recently transitioned from the world of video and motion graphics to the exciting field of product design at Mantra Labs. When she’s not designing, she enjoys watching movies, traveling, and sharing her experiences through vlogs.

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