The benefits of artificial intelligence in the healthcare industry | HCLTech

The benefits of artificial intelligence in the healthcare industry

Amid the meteoric rise of ChatGPT, AI has been quietly driving a revolution in the healthcare industry
13 minutes read
Jaydeep Saha
Jaydeep Saha
Global Reporter, HCLTech
13 minutes read
The benefits of artificial intelligence in the healthcare industry

There’s no stopping the growing use of artificial intelligence (AI) as scientists, researchers, doctors and AI experts have been unlocking its usability and benefits in the healthcare industry. Innovations and groundbreaking treatments are being developed using this technology, providing a beacon of hope for millions of patients across the world.

Take for example, Acinetobacter baumannii, which is one of the most problematic species of bacteria that can infect wounds and cause pneumonia. The World Health Organization has identified this superbug as a “critical” threat as it can shrug off multiple antibiotics and survive on surfaces and medical equipment, while Dr Jonathan Stokes from McMaster University described it as “public enemy number one”.

However, recently, scientists—with the help of AI that helped narrow down thousands of potential chemicals to a handful for tests—have discovered a new antibiotic called abaucin that can kill the superbug. Still in its nascent stage, the drug will need to undergo further tests before being used.

“AI enhances the rate, and in a perfect world decreases the cost, with which we can discover these new classes of antibiotic that we desperately need,” Dr Stokes told the BBC. The development of abaucin is the latest example of how AI can be a revolutionary force in science and medicine, with researchers in Canada and the US confident that AI has the power to massively accelerate the discovery of new drugs.

The structure of human proteome

With the help of DeepMind’s AI program, AlphaFold, which makes it possible to search for the 3D structure of proteins, researchers have gone beyond the traditional techniques, including X-ray crystallography and cryogenic electron microscopy (Cryo-EM), and predicted the structures of 350,000 protein structures, which include 20,000 in the human proteome.

“It takes a huge amount of money and resources to do structures. It was taking us six months per structure and now it takes a couple of minutes. We couldn’t really have predicted that would happen so fast. When we first sent our seven sequences to the DeepMind team, two of those we already had the experimental structures for. So, we were able to test those when they came back. The structures [AlphaFold] produced were identical,” Prof John McGeehan, a structural biologist at the University of Portsmouth, told the BBC.

Besides making the data freely available to users for any purpose, AlphaFold and the European Molecular Biology Laboratory’s European Bioinformatics Institute have expanded the database by more than 200-fold to over 200 million structures.

Applications of the AlphaFold system include combating antibiotic resistance, accelerating the discovery of drugs for neglected diseases, developing a novel malaria vaccine, shedding light on genetic variation, gauging the impact of rotavirus on gastroenteritis, studying the nuclear pore complex and contributing to drug development for cancer and neurological disease.

“We believe it’s the most complete and accurate picture of the human proteome to date. We believe this work represents the most significant contribution AI has made to advancing the state of scientific knowledge to date. And I think it’s a great illustration and example of the kind of benefits AI can bring to society,” Dr Demis Hassabis, chief executive and co-founder of artificial intelligence company DeepMind, told the BBC.

The mind reader

Jut out of the realms of science fiction fantasy, a research team in Singapore has used AI and a scanning machine to develop basic mind-reading techniques that decode what a person is mentally picturing, while reproducing representative images.

Based on the same principles and language model technology of ChatGPT, Zijiao Chen, who is a PhD student at the National University of Singapore (NUS) and one of the lead researchers in the team, compared their technology to a “mini GPT for the brain” that leverages a large-scale dataset from an fMRI “to learn how our brain interprets and thinks”.

Signals generated from brain scans or fMRI (functional magnetic resonance imaging machine) of participants—looking at pictures from a dataset of 160,000 images for over 18 hours—are then put through the AI model, MinD-Vis, to train it to associate certain brain patterns with image features. The language model then recovers unseen visual stimuli from new images that participants were shown based on analysis of their brain activity.

“In other words, MinD-Vis is able to read and reconstruct images from our minds. Decoding reaches vital information that plays a role in understanding how our brain processes and interprets the world around us. It helps researchers to visualize and unlock the mystery of the brain and a deeper comprehension of its complex functions,” Chen told The Telegraph. He added that that it does not reproduce 100 per cent accuracy, but recognizable matches and significantly out-performed previous experiments of a similar nature.

While professor of neurobiology at Columbia University, Rafael Yuste told The Telegraph that such a scientific progress was “fantastic for patients and incredibly important for researchers trying to understand how the brain works”, he simultaneously warned that it could also be weaponized and used for military applications or for nefarious purposes to extract information from people.

Paraplegic patient walks with AI magic

Magic or pure science, a paraplegic patient just thought about moving his legs and technology did the rest. Using algorithms based on adaptive AI methods, researchers created a “digital bridge”—between brain and spinal cord—while decoding real-time brain signals from an electronic device placed atop the patient’s head (cerebellum) and transmitting them to a neurostimulator connected to an electrode array over the spinal cord, which controls the leg movement.

Researchers, including the project’s neurosurgeon Jocelyne Bloch and Guillaume Charvet, head of brain-computer interface research at French public research body CEA, said the breakthrough will enable doctors to bypass damaged nerves and boost the treatment of a range of neurological disorders, including strokes. However, much research and development will be required to miniaturize and enhance the technology, cut production costs and carry out extensive clinical trials.

Now with the ability to regain natural control over the movement of his limbs, patient Gert-Jan Oskam can now walk and climb stairs. He told the Financial Times: “This simple pleasure represents a significant change in my life. This feels radically different. Before I felt that the stimulation was controlling me, now I am controlling the stimulation myself. I can take steps that feel natural.”

HCLTech’s healthcare solutions

Having won the IoT Breakthrough Award in the IoT Health & Wellness Innovation of the Year and Everest Group PEAK Matrix ‘Service Provider of the Year™ award for its life sciences and healthcare practices, technology leader HCLTech has focused on three main areas: enhancing consumer experience, improving care delivery and generating value across enterprise with its cutting-edge technologies that include AI, Data and Analytics, IoT, Product Lifecycle (PDLC) Management and Digital Process Operations.

“The real value of a digital ecosystem in healthcare systems is an integrated intelligence platform that can address the product value chain, clinical workflows and operations value chain together. We are seeing many MedTech companies move in this direction to build a comprehensive process intelligence platform that can integrate both clinical and service workflows,” says Partha Marella, Executive Vice President and Global Head of Medical Devices and Manufacturing segment at, HCLTech.

“HCLTech recently helped implement such a platform for a global IVD company to drive its business objectives right from shortening the compound research time, to finding improved therapeutic processes by analyzing large amounts of genomic data to providing custom therapy for patients based on insights derived from molecular biology samples."

Looking at another example, Marella comments: "HCLTech helped a leading sterilization equipment company that opted for an AI-powered service intelligence platform to gather sensor data in real time from across all its customer base and predict potential component failures. Besides predicting potential failures, these AI- and IoT-powered models also determine if a component requires replacement or service—thereby increasing efficiency and reducing just-in-time service.”

Other AI benefits in healthcare

Apart from the innovations mentioned above, here are some more examples of how AI is transforming the healthcare industry.

Designed to help detect polyps, GI Genius is an AI-assisted colonoscopy tool that helps physicians place green boxes around areas that may need extra scrutiny—as it may lead to colorectal cancer—during the diagnostic imaging procedure. Medtronic has partnered with Nvidia to distribute this worldwide, allowing third-party developers to train and validate their AI models using the AI access platform.

To analyze heart sound and provide physicians with a full cardiac assessment of patients in under five minutes, Los Angeles–based Sensydia designed an AI-powered non-invasive Cardiac Performance System (CPS) device that recently completed enrollment in a 225-subject development study for the AI device, which has undertaken multiple clinical studies.

“AI is transforming cardiac failure screenings with an ability to accurately detect types of cardiac problem and stratify risk. Prior to AI-driven solutions, specialists had to identify potential problems by analyzing ECG wave forms—sometimes leading to oversight errors and failure to observe minute patterns. HCLTech’s AI solutions—trained on several hundred thousand of ECG wave forms—help in localizing the problems quickly and improving therapy efficacy,” adds Marella.

Designed for trans-radial users, Ottobock’s Myo Plus pattern recognition represents a new paradigm in the control of a myoelectric prosthesis or robotic prosthetics. Uniting advanced AI algorithms with the intuitive and innate EMG signals of the user, Myo Plus adapts to their natural movements involving discreet electric signals from their muscles, instead of requiring the user to adapt to the system.

Designed to provide enhanced visualization along with real-time and on-demand surgical insights in the operation theatre, Activ Surgical in January announced that it completed the first AI-enabled ActivSight operation on December 22 last year at the Ohio State University Wexner Medical Center using its ActivSight Intelligent Light product. This product is compatible with laparoscopic and robotic systems and integrates with standard monitors.

Rolling out its AI-powered surgical navigation system into operating rooms to collect data, Seattle-based Proprio’s Paradigm platform is the first to use “light field technology” in spine surgery. The US Food and Drug Administration has recently approved the new platform and now spine surgeons will be able to operate more efficiently. The startup said it has placed its Paradigm system in several US operating rooms to capture surgical data that will ultimately help surgeons improve how they perform procedures.

Edison is GE HealthCare’s new AI-powered vendor-agnostic hosting and data aggregation platform that aims to enable the easy deployment of clinical, workflow, analytics and AI tools, connecting devices and other data sources via cloud, edge or directly onto smart devices into an aggregated clinical data layer. The Edison apps can integrate and assimilate data from disparate sources, and apply analytics or advanced algorithms to generate clinical, operational and financial insights.

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