Augmenting the smart health devices of the future

Recent years have seen enormous strides in artificial intelligence (AI) and machine learning (ML). While both have been around for years, advancements in computing have seen their capability expand exponentially.

Life sciences has been one area that benefited from this in spheres such as drug discovery, disease diagnosis and personalised medicine. AI and ML even contribute to robotics in surgery, enhancing precision and ensuring minimally invasive procedures.

This is not to mention also easing the high levels of burnout among healthcare practitioners due to the demanding nature of their work, exacerbated in recent years by clinical staffing shortages across the board.

Thankfully, AI in healthcare is starting to address this and help people in their work, says Srini Shankar, chief business officer of GlobalLogic.

“AI can automate routine administrative tasks, such as appointment scheduling, billing and documentation, allowing healthcare practitioners to focus more on patient care,” Shankar says.

“Medical transcription is undergoing a seismic transformation, with AI-powered speech recognition tools transcribing spoken words into text, streamlining the creation of medical documentation with higher quality and accuracy.

“By automating routine tasks and providing decision support, AI can help reduce the administrative burden on healthcare practitioners, potentially lowering stress and preventing burnout, and improve the overall healthcare system by increasing the amount of quality time spent with patients.”

AI takes many forms, with GenAI providing broader applications such as virtual health assistants, literature mining and data/document preparation.

One of the examples Shankar provides is GlobalLogic’s work with a client in clinical trials employing AI and ML to analyse patient data and identify potential outliers that could impact study outcomes.

Leveraging computers to detect patients needing attention can optimise human intervention.

Other examples include an AI-enabled parser, which dissects clinical trial protocols and assembles tailored study plans for different roles. It also uses ML to identify factors influencing a patient’s hospital stay duration, predict length of stay and use real patient data to identify outliers early and take corrective measures.

The benefits of AI and ML are clear with their rapid evolution, thanks to the increasing reliance on vast amounts of data for AI and ML solutions. Shankar says this data is instrumental in algorithm development and training, synergising with the trend of enhanced computer power, notably through cloud computing.

He says a noteworthy development is the concept of GenAI, a specialised subset focused on leveraging natural language processing for both input and output in AI and ML interactions. The game-changing element allows users without programming experience to directly engage with AI, asking queries in normal language and receiving human-like responses.

“This human language interface streamlines complex interactions, allowing users to extract insights efficiently,” explains Shankar. “It’s crucial to address the necessity for guard rails — best practices, rules and regulations — in the accelerating landscape of AI. As AI capabilities expand, controls need to uphold privacy, confidentiality and ethical data use.

“The challenge lies in striking a balance, ensuring that while AI solves intricate problems, decisions requiring human judgment remain under human purview. The evolving nature of this complex topic requires ongoing consideration and adaptation.”

Much of the technology is set up to help AI and ML to thrive. Smartphones are now more powerful than desktop computers from a few years ago. At the same time, advancements in sensors, power and communications have greatly improved wearables, ensuring that they’re unobtrusive while allowing the real-time measurement of vital signs and potential biomarkers.

This provides significant potential for advanced AI algorithms to analyse this data and provide significant findings, says Shankar.

“They could detect early signs of cardiac conditions, predict the need for insulin doses, warn of potential breathing issues, or even administer therapy,” he said. “When this data is aggregated on a large scale, there’s potential for developing new treatments, establishing gold standard protocols and efficiently tailoring healthcare for diverse patient populations.

“The synergy between sensors, devices, data and AI algorithms continuously refines diagnostics and care.”

These devices have almost limitless potential to advance healthcare, which GlobalLogic is well-placed to realise.

It focuses on three main areas: the design and development of next-generation connected devices, the collection, curation and exploitation of data from all sources, and the design and development of world-class digital experiences that leverage those systems to improve the health of individuals.

The organisation has over 2,000 engineers, designers, architects, testers and business analysts. It is dedicated to the healthcare market and looking to understand and solve problems and embrace opportunities for its clients.

“Thanks to our 20-plus year track record in healthcare, we can often bring unique and stress-tested approaches to a given situation,” he said. “Often, our engagements begin with an advisory designed to help our clients fully understand the situation, fill in any gaps, explore potential alternatives and make recommendations on a path forward and next steps.

“We look to align ourselves with what our clients need in a given situation. We try to configure ourselves like the missing piece of the puzzle.”

The organisation is mission-orientated, focused on successful outcomes, and creates tailored engineering labs or digital labs designed to deliver ongoing value transparently.