With applications across diagnostics, wearables, wellness and lifestyle management, and virtual assistants, AI is changing healthcare systems. In addition, the COVID-19 pandemic hastened the implementation of AI in healthcare. Pharmaceutical and biotechnology companies, in particular, quickly adopted AI to hasten drug discovery and development.
The global cry to reduce healthcare costs, availability of big data, new innovations and the mayhem of the pandemic has already expedited the adoption of AI applications across various healthcare segments.
In a research from Accenture, in the US alone, the implementation of key clinical health AI applications will estimatedly create annual savings of $150 billion by 2026.
Fundamental AI technologies that will drive change in the healthcare sector
Machine Learning: ML is increasingly being used to automate data analysis. New strides in ML will simultaneously amplify supervised learning, deep learning, unsupervised learning, and reinforcement learning.In healthcare, machine learning will improve precision medicine, imaging, diagnostics, and drug discovery
Natural Language Processing (NLP): Internet, connected devices, and data availability have helped develop both the statistical and semantic aspects of NLP in recent years. As healthcare companies intend to structure and interpret their patient data more accurately, NLP applications will continue to rise.
Computer Vision: Computer vision system is the driving force behind robotic surgery. This technology allows for precise diagnosis and reduction in false positives. With the potential to eradicate medical procedures and therapies, robotic surgery applications will see tremendous growth in the future of healthcare.
AI applications providing value in healthcare
According to Accenture, the three top categories where AI applications show the most promise for the near future are robot-assisted surgery, virtual nursing assistants, and administrative workflow assistance.
Robot-assisted surgery has the potential to deliver more precise results, from guiding the exact trajectory of the physicians’ instruments to gleaning insights from previous surgeries. Robotic surgery can reduce a patient’s length of stay by 21 percent.
Virtual nursing assistants will ease the burden of medical professionals by remotely assessing patient symptoms, reducing unnecessary visits, and delivering precise and timely clinical alerts. These AI applications can reduce RN time by 20 percent.
Virtual workflow assistance could completely eradicate activities such as writing medical notes and prescriptions and ordering diagnostic tests completely from the medical professional’s to-do lists. This could lead to 17 percent time savings for doctors and 51 percent for nurses.
One aspect of AI solutions is their ability to adapt and perform new tasks as they gain experience. Like Biobot Analytics, co-founded by our Leading Health Tech Innovation course guest speaker Newsha Ghaeli. AI-powered health tech company, Biobot Analytics tracks wastewater-based epidemiology. The AI application started tracking the spread of Covid-19 at the onset of the pandemic.
Regardless of how AI heath tech apps evolve, we know that it will permanently change the way healthcare is delivered. We’ll discuss these changes in part II of this blog, coming next week.