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AI in Healthcare: Driving the Future of Medical Innovation

In 2017, a mere 65 AI startups in healthcare were recorded. Fast forward five years to 2023, and this number had ballooned to over 300. These numbers are not just a testament to the growth of AI but highlight its profound impact in transforming healthcare.

Such an influx of AI solutions in healthcare signifies a transformative shift towards precision, efficiency, and personalization in patient care. Innovations range from improved diagnostics and personalized treatment to advanced patient monitoring. Today, we delve into the revolution led by AI in healthcare, spotlighting some groundbreaking developments that are shaping the future of medicine.

Pioneering Diagnostic Accuracy with AI

Prompt and precise disease identification is pivotal in healthcare. AI in healthcare is leading a revolution in this arena. The trailblazers include innovative firms like Mantra Labs, as well as projects like an AI-powered system for medical imaging and a cutting-edge pathology platform.

  1. UI/UX: Mantra Labs, global tech innovation firm has worked extensively in building AI-powered technology solutions for business-specific problems. Their solutions, such as intelligent clinic management systems, customer portal apps, and more illustrate their innovation and commitment to enhancing digital experiences through AI.
  2. Medical Imaging: An AI system developed by DeepMind, a project known for pushing the boundaries of AI, has demonstrated its superior precision in detecting breast cancer from mammograms, reducing false positives by 5.7% and false negatives by 9.4%. This advance not only promotes more accurate diagnoses but also significantly alleviates patient anxiety.
  3. Disease Detection: PathAI, a startup with a focus on pathology, uses AI to identify diseases such as cancer with more accuracy than human pathologists. This can lead to early detection and therefore more effective treatment planning.
With AI, we’re seeing a paradigm shift in healthcare, opening a world of possibilities for timely and precise disease diagnosis.

AI: Personalizing Treatment

AI in healthcare is dispelling the ‘one size fits all’ approach in treatment strategies, steering us towards personalized medication and therapies.

Question: Can AI pave the way for a new era of personalized medicine and expedited drug discovery?

AI: Enhancing Patient Outcomes

AI’s role in healthcare extends beyond diagnosis and treatment. It plays a significant part in continuous patient monitoring and predicting future health trajectories.

  1. Telemedicine: Innovative telemedicine platforms like Aidoc use AI for the real-time monitoring of patient data, alerting healthcare providers about significant health changes.
  2. Predictive Analytics: AI can scrutinize a patient’s health records to forecast future health risks, enabling early intervention and prevention. Google’s DeepMind is spearheading this initiative with its project that predicts patient deterioration up to 48 hours before it happens.
  3. Mental Health: AI can also help healthcare providers in the treatment of the mental health of their patients. Wysa, a mental health app developed by Mantra Labs uses emotionally intelligent AI to help users cope with stress, anxiety, depression and other challenges. 
Can a major healthcare operations be automated using AI?

Table 1. Notable Contributions of AI in Healthcare

AreaInnovative SolutionsImpact
1.Disease DiagnosisDeepMind’s AI systemReduced false negatives by 9.4%
2.Personalized TreatmentIBM Watson’s Oncology platformIndividualized cancer treatment
3.Drug DiscoveryInsilico Medicine’s AI-driven drug designDramatically reduced drug discovery time
4.Patient MonitoringAidoc’s telemedicine platformReal-time patient data monitoring
5.Predictive AnalyticsDeepMind’s patient deterioration predictionEnables early intervention and prevention
6.Mental HealthWoebot’s cognitive behavioral therapySupports users in managing mental health

AI in healthcare is charting a future where diagnoses are swift and accurate, treatments are personalized and effective, and patient outcomes are significantly improved. The journey, however, has just begun, and there is much more to explore and innovate.

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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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