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Reimagining Medical Diagnosis with Chatbots

4 minutes, 51 seconds read

Chatbots are rapidly gaining popularity in the healthcare sector. According to research conducted by Grand View Research, the global chatbot market is expected to reach $1.23 billion by 2025 growing at a CAGR of 24.3%. The current COVID pandemic has caused a lot of stress in the healthcare sector, with hospitals getting swamped with COVID-19 patients and also handling regular consults. 

This has made medical chatbots very attractive, helping in scheduling appointments, custom support, symptom checks, providing nutrition and wellness information, mental therapy, etc. Let’s take a look at how chatbots are transforming the digital transformation in the healthcare sector.

The shift to Medical Chatbots and Telemedicine

Lockdowns and social distancing due to COVID-19 gave a significant boost to digital business models. Organizations had to find ways to keep up the operations, make business continuity plans, and engage the workforce working remotely. Even healthcare providers took to technology such as telemedicine, chatbots, and remote monitoring equipment for patients who were not able to visit doctors in person. 

Many hospitals had been trying to implement telemedicine over the last couple of years, at least for ailments that can do without in-person diagnosis and can be cured by prescribing medicines based on symptoms told by the patient. COVID-19 gave that extra push for telemedicine. 

Another tendency that people have these days is to search for information on Google for self-diagnosis. However, that may not be effective. Therefore, many people are turning towards healthcare chatbots for medical information. 

Multilingual AI chatbot with video for diagnostic services – Hitee.chat

The Role of Chatbots in Medical Diagnosis 

The entire experience from admission to discharge is one of the key differentiators for patients while choosing a healthcare provider. People want quicker services and instant answers to their queries. 

With the coronavirus outbreak, hospitals and clinics are facing additional pressure. It has created a dire need for technology such as medical chatbots to provide better patient experience. 

Currently, there are some chatbots that leverage AI and machine learning to provide diagnoses by using algorithms to run the responses through a database of medical literature available. Let’s take a look at possible situations where chatbots play a crucial role in diagnostics-

  • Reliability: Instead of using a search engine to find answers, people will find chatbots more reliable for medical information. They need to be backed by legitimate medical databases to provide better accuracy.
  • Medical History: Chatbots cannot replace the role of a doctor while diagnosing but it can be of great assistance to them in providing medical history to better diagnose the health issue.
  • Triggering Attention: There are many symptom checking apps and bots available today which are widely used to check symptoms for possible diseases. Even with the nearest possible result in hand, it triggers the patient to a doctors’ visit if the symptoms seem grave. 
  • Support for Healthcare Workers: In case of mild diseases such as common cold, indigestion, minor wounds, etc. Chatbots are of great help as they reduce the workload of health workers who can focus on critical patients. 
  • Ensure Confidentiality: In some cases, patients may not be comfortable to open up to a doctor in person, but finds it easier to answer questions by a chatbot. Especially, when it comes to mental illness. 
  • Availability: Although rare, but there can be cases when medical help is not available physically such as during curfews or lockdowns. In such situations chatbots can be of great help for immediate medical support. 

Prevailing Challenges

Chatbots can provide basic medical information or do a cursory diagnosis of a health problem. However, the biggest challenge with diagnostic chatbots is the accuracy of the output. 

Research by the National Center for Biotechnology Information (NCBI) suggests that computer-based diagnostic support tools can be very beneficial to clinicians. But the effectiveness of 23 symptom checkers reported deficits and only 34% of standard patient evaluations were achieved in the first attempt. 

Unlike actual doctors, chatbots cannot feel the pulse, check the heartbeat or blood pressure, check the body part where the issue is, etc. Patients these days tend to self-diagnose quite often but they may not understand the diagnoses. 

Medical Chatbots can provide the information but can they explain it like a doctor as well? That would be debatable. Not everyone can understand medical jargon. Another issue is the risk of error in diagnosis. Too much dependency on the diagnosis can have steep consequences putting lives at risk. 

Redefining Chatbots in Medical Diagnosis

Currently, the chatbots function primarily through text while chatting with the patient. But in the coming future, it has a huge scope of improvement when combined with videos, images, voice recognition it will provide better information to the chatbot to provide better diagnoses. 

Medical diagnosis chatbot with video – Hitee.chat

Technologies like Natural Language Processing (NLP), machine learning, AI algorithms will enable better processing of the data and help clinicians with quicker diagnosis. It is possible to increase the capability of these chatbots through broader data and technologies. NLP integrated chatbots can also cater to specially-abled patients. 

More usage of diagnostic chatbots will make people take better care of their health. Indeed, there is scope for improvement for chatbots in medical diagnosis. But at the same time, reliability on them is also gradually increasing.

Down the Road

Chatbots in medical diagnosis can act as an aid to clinicians, reduce workload for healthcare workers, provide instant answers, and in some cases, it is a cheaper medium and lesser hassle than to visit a hospital. 

Bots have huge potential to streamline diagnosis. It won’t be a surprise to see chatbots be the first point of contact for medical help. 

We’ve introduced a multilingual AI-powered video chatbot for hospitals, private clinics, and diagnostic services. It can automate appointment bookings, checking symptoms, provide information, answer FAQs and more. You can write to us at hello@mantralabsglobal.com for your specific requirements.

Website: Hitee.chat

To know more about how HealthTech is reshaping the healthcare industry in bringing hospitals to a customer’s doorstep, watch our webinar on Digital Health Beyond COVID-19

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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