Contact us:
040 4016 5703 099 6344 0404
Follow us:

How data analytics is changing the world of the healthcare industry

Continuous patient monitoring is critical for enabling timely medical interventions, reducing readmission rates, and improving health outcomes, and advanced analytics will play a central role in it.

It is vital for any industry to lean on data to make better-informed decisions at the consumer and business level. In the world of healthcare, there is massive data that is collected which is not just limited to the business processes and procedures, but also to large amounts of patient health data.

In the article below, we discuss the impact Data analytics and AI technologies create in healthcare, determining solutions for a better and healthier tomorrow.

Faster responses to future crises

The ability to apply machine learning & analytical algorithms on volumes of data in a scalable way enables quicker response for any future pandemic. We’ve witnessed it during the initial days of the recent one.

Moderna, one of the first drug makers to produce a COVID-19 vaccine (mRNA), has built a technology platform to quickly and safely deliver the drugs. The platform behaves like “an operating system” (host) to spin up new “apps” (drugs) which can be analyzed, simulated, tested, and delivered simultaneously. Moderna had been initially working only on a “test” using the platform to demonstrate how quickly they could develop a vaccine for a future virus in the event of a pandemic, soon they faced a real-world challenge when COVID-19 took the world by storm and had to act swiftly and develop a vaccine to save millions of lives.

Using the apps & machine learning capabilities built on Cloud, the team designed a vaccine in just two days, and within 42 days the first vaccine was ready to undergo clinical trials, which would otherwise take 20 months to develop.

Enabling Innovative solutions

The experimental nature of a big data analytics exercise yields innovative solutions to problems that were not much explored before. One of the intriguing healthcare startups we work with is a holistic care provider for special needs children affected by Autism, ADHD, and other developmental delays.

The startup built and tested a minimum viable product with AI capabilities, which would analyze the child’s actions and facial emotions in real-time to provide quick insights so that the progress of the therapy can be recorded and tracked.

Mixed Reality in Healthcare

Our internal Hackathon seven years ago saw an amusing yet thought-provoking prototype for Augmented Reality. It combined AI and AR technologies and put them into use on Fetal Ultrasound Scan images and offered the user a simulated 3D view of what the baby would look like when the ultrasound scan image is viewed through the camera.

With the new range of XR devices emerging, interesting applications such as visualizing scan images, viewing internal anatomy during a surgical procedure, or applying AI analytics on live streams of the skin or body surface that are viewed through the XR device for diagnosis could soon be a reality.

Improved Patient Care & Engagement\

A software and wearables company developed a highly-secure continuous monitoring solution for diabetic patients who are at high risk of lower limb amputations by designing a connected boot (wearable IoT) to reduce the rate of limb amputations. IoT analytics coupled with increased use of wearables will become part of regular patient monitoring routine resulting in quicker decision-making and proactive care.

Recent news also suggests that in a preliminary study conducted, researchers were able to predict 10 years probability of a person having a heart attack through deep learning applied over chest X-ray images.

Continuous patient monitoring is critical for enabling timely medical interventions, reducing readmission rates, and improving health outcomes, and advanced analytics will play a central role in it.

Role of Edge AI

With its ability to deliver real-time analysis of big data, edge AI will become a critical enabling technology in multiple healthcare scenarios. Robots and intelligent systems are already being developed for elderly care to support them in scenarios such as fall detection. In such cases, analytical algorithms run at the edge to provide speedy results.

No Comments Yet.

Leave a reply