Asokan Ashok, Founder & CEO, UnfoldLabs Inc.

Asokan Ashok is the CEO of UnfoldLabs. He is an expert in driving customer insights into thriving businesses and commercializing products for scale. As a leading strategist in the technology industry, he’s excellent at recommending strategies to address technology and market trends. Highly analytical and an industry visionary, Ashok is a sought-after global high-tech industry thought leader and trusted strategic advisor by companies.


We are on the cusp of a perfect storm of technology, products, solutions, leadership and human intelligence that is shaping our healthcare for the greater good. Indeed, technology is transforming our lifestyle, work habits, and relationships. In addition to creating new opportunities for humanity to flourish with better health, technological advances are helping life, safety, security, and protection for humanity which are hard to predict with innovations happening on multiple fronts.

Advances in devices and software have transformed healthcare settings into state-of-the-art environments, with advanced visualization aiding surgeons and robotics through insightful analytics. This has driven improved medical, operational, clinical and financial outcomes across the healthcare spectrum. With technology adoption happening in healthcare at a faster pace, about 80% of hospitals and medical practices plan on, or already have artificial intelligence (AI) solutions. 

Though AI leverages computing and machines to mimic the problem-solving and decision-making capabilities of the human mind, it’s defined as the science of making machines intelligent with software. AI combines computer science and substantial datasets, as well as disciplines like deep learning, machine learning, and robotics. These technologies use algorithms to build expert systems that make predictions or categorize data based on input. 

Listed below are 5 areas where AI will be used in healthcare:

AI in Healthcare 1: Diagnosis & Medical Imaging

Imaging in healthcare involves sophisticated ways of analyzing every data point to distinguish a disease’s location. If the first few decades of medical imaging were about refining the resolution of the pictures taken of the body, then the next decades are dedicated to interpreting the data. 

Imaging has evolved from its initial focus, diagnosing medical conditions, to playing an integral part in treatment, especially in cancer. Doctors are looking for more help with imaging to help them monitor tumors and the spread of cancer cells. With better outcome with imaging technologies, the role of AI will transform the types of treatments patients receive.

AI in Healthcare 2: Precision Medicine

This decade, precision medicine used biomarkers, such as IL-6 and c-reactive protein, to assess the severity of the disease and create various therapies to evaluate the efficacy of vaccines. Precision medicine is also finding its place in managing infectious and chronic diseases. Genome‐informed prescriptions is one of the most important areas which will demonstrate the power of precision medicine at scale. 

The convergence of AI and medicine will be able to prescribe the right drug to the right patient in the right dose at the right time, avoiding harm to the patient. The scope of precision medicine has increased immensely with AI development in the fields of genetics, molecular biology, and biochemistry.

AI in Healthcare 3: Robotic-Assisted Surgery

Robots, in the past were usually used in healthcare mostly to conduct more precise and less intrusive surgeries from a distance. The surgeon would be positioned behind a console, view magnified images on a screen, and control robotic arms and tools. With AI, the robots of today are now autonomous, flexible, and have the ability to self-learn with machine learning and deep learning techniques. Surgeons want robots to monitor any change in the operating rooms, detect errors, and react to emergencies. To achieve this, robots leverage advanced AI solutions, which include the following technologies:

  • Pattern-Recognition Solutions: A robot is trained with surgical procedures. Robots with AI technologies can learn a pattern, replicate it with advanced precision, and can adjust its actions in real-time. For example, a robot is trained in tissue removal patterns. The robot alters its surgical plan if it detects tissue deformations during the surgery.
  • Deep Learning (DL) Solutions: DL algorithms increase the autonomy of a robot through its training, incorporating scenarios from before and after an operation. Let’s imagine that a robot is used for surgery on a patient with chronic kidney disease. By going through the pre-operative planning stage and detecting abnormalities from CT scans, the robot can predict kidney failure risks during the procedure. If it detects bleeding, it adjusts to save the patient’s life.
  • Computer Vision (CV) Solutions: CV can detect patterns in images (3D images and scans) and video during surgery. For example, AI driven robots are trained to classify, recognize, and identify suturing gestures and can repeat them with greater accuracy during surgery.

AI in Healthcare 4: Drug Discovery

AI can be a powerful asset in the discovery & innovation of of small-molecule drugs, that provides access to novel biology and chemistry, increased success rates, and more cost-effective discovery processes. AI can revolutionize the established workflows of drug discovery teams’ by providing invaluable insights and tackling numerous challenges and constraints posed by traditional R&D.

AI is transformational not just for medical providers and patients. There’s an immediate 20% to 40% reduction in costs for preclinical development that could generate the cost savings needed to fund the successful development of 4-8 novel molecules. This is expected to represent a 15% increase in approved therapies, novel, and innovative drug approvals.

AI in Healthcare 5: AI-Powered Virtual Assistants

Intelligent virtual assistants (VA) are revolutionizing how care providers engage with patients. These virtual healthcare assistants provide current and accurate data to help patients navigate through any support they need or allow them to book appointments. Hospitals can create a more personalized ecosystem for their patients with AI-powered chatbots that can help across patient care journeys. 

The realism of VA technology in healthcare is growing as algorithms are being utilized to detect emotions through natural language processing. In addition, image recognition is used to process images, handwritten scripts, and QR barcodes. These features give a well-rounded picture to the VA, enabling it to perform more accurately. 

My Predictions for AI in Healthcare

Prediction 1: AI for Hospital Administrators

From enhancing patient experience to improving healthcare processes, robotic process automation (RPA) will drive the healthcare system to a brighter future. With RPA, it’ll become possible to streamline the healthcare system, enhancing the efficiency and quality of services provided in the healthcare industry. Besides, as a healthcare administrator, automating healthcare systems will offer real-time data to support decision-making.

Prediction 2: Virtual Assistants for Customer Support

Virtual assistants can facilitate the effortless automation of many administrative duties, including registering new patients & referrals, maintaining & updating patient records, scheduling appointments, following up with patients, managing staff shifts, confirming insurance documents and filing claims, medical billing, and keeping medical records, etc. Furthermore, integrating intelligent VAs will help healthcare organizations to increase efficiency and enhance patient experiences.

Prediction 3: AI for Predictive & Proactive Maintenance

As data volumes in hospitals continue to grow, with data from more digital platforms, medical devices, and wireless sensors, understanding how to connect equipment fleets and ensure their performance is strategically advantageous. By leveraging more algorithms in hospital equipment fleets, opportunities will arise to design and develop new operating models, such as pay-by-use or subscription-based services, where service activities can depend on the number of patients being treated.

Final Thoughts

I’m personally excited at the possibilities of AI making a huge impact on our world. I don’t see AI peaking in my lifetime, as it still has a long way to go. The future of AI and digital health is full of potential. With the development of AI, we’re at an incredible revolution in healthcare. AI is already used to diagnose diseases, interpret medical imaging, and monitor patients. It’s also being used to develop new drugs and treatments, as well as to automate the processes of medical research. This technology will revolutionize healthcare and provide better outcomes for patients. 

With digital health, we can see a future where we can access more personalized healthcare tailored to individual needs. This could transform the way we access and manage our health. Finally, humanity will remain the cornerstone of healthcare, as it always has been. With the development of AI and digital health, humans will continue to be the primary medical knowledge and compassion source.

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