AI needs more doctors and data scientists. AI in healthcare is set to be a game-changer in the way smarter technologies are adopted for saving lives.
Artificial Intelligence (AI) has been the savviest technology of the century. Its proliferation into our daily lives and businesses has put many mundane things into oblivion. From correcting texts on your screen to asking for Smart Home automation, there is AI everywhere and in everything we do today.
In this article, we bring to you how AI in healthcare is setting its pace for the New Year and what technologies would be a regular feature in the health centers that you visit.
But, first — here’s a quick stat check from AI in healthcare industry.
- “Key clinical health AI applications can potentially create $150 billion in annual savings for the US healthcare economy by 2026.” – Accenture
- Acquisitions in AI for healthcare companies would increase significantly, contributing 40% CAGR through 2021-2022.
- The rise of AI-as a-Service in healthcare and pathology is an indisputable trend set to blow the economy with the sheer volume of data and revenue churn.
- AI needs more doctors and data scientists. There would be 10X more requirements for both professionals.
- There would be more reliance on AI as a pharma consultant and advisor in 2025-2030.
- Diagnostics and image recognition would be the biggest driver of healthcare AI deals in 2020-2025.
These are few areas that research analysts have strongly guided their senses in AI for healthcare. As we near the end of the first two decades in the century, we believe that this (read below…) is what is going to change the healthcare industry forever.
As AI gets more sophisticated and faster in processing data, there is a considerable option of letting the technology take care of Medical Research and Analytics. In medical research, AI can analyze complex and Big Data pools faster and more precisely with an unprecedented rate of accuracy for relevant studies and categories. It would also help healthcare facilities to match patients’ needs with the exact clinical study required to fully understand the disease and diagnosis.
Genealogy and Immunotherapy
For a trained genealogy expert, it would take decades of extensive study and research to map the ancestry and parents of five billion people on the Earth. It is currently churning genealogy data at one person per minute. With so much data available for study in healthcare related to gene therapy and immunotherapy, AI and Machine Learning algorithms could further simplify the process.
For companies like Ancestry.ai, the field of AI in healthcare could get a massive boost in the right direction as we rely on genealogy data for study in gene defects and impact on immunotherapy.
Empowering Radiology with Intelligent Diagnosis
Healthcare is dependent heavily on radiology innovations. And, here AI is a big asset. While AI has been here for some years now, its value in healthcare radiology is only beginning to be fully understood since 2015.
While the use of AI and machine learning in radiology is still in its nascent, largely due to the lack of high-quality data sets, we see a potentially high-traction industry developing in this specialized area of healthcare. The use of voice and chat bots, together with Neural Networking and AI-based image recognition could readily provide high-quality pixel-corrected images in detecting cancers, brain injuries, strokes and other health hazards.
Surgical outcomes would be 99% successful with robots taking on the mantle of surgeons. The guided surgical processes would be directed by trained surgeons who understand the scientific and ethical limits of dealing and working with non-human interfaces.
The benefits of robo-surgeons are many, but counting the top five that made the cut here with us:
- Delivering higher accuracy in micro-surgical procedures
- Reducing human fatigue in long surgical processes
- Reducing the chances of advanced post-operative procedures
- Dealing with real-time data that radiology and pathology departments could have missed
- Reducing surgical mortality rates
Overall, robo-surgeons are like an extension of the human arm that are better equipped to deal with the micro-movements needed to reach the deeper incisions. The Machine Learning and AI tables also take care of the surgeon’s physical tremors experienced due to fatigue or lack of focus, thereby, ensuring 100% accurate procedure.
AI Personalization and Wearables in Patient Care
In the era of personalization in everything, how could healthcare be far. AI in healthcare would deliver the promising results in personalization via wearables and AR-VR-based interactions. Wearable technology in healthcare would further diversify the mission of bringing smarter technologies into the realm of public health. The demand for well-organized and patient-focused healthcare is driving the demand for remote clinical trials, powered by AI technology, primary mission here dealing with wellness and fitness programs.
Creating AI journeys for radiology practitioners could be the biggest goal for a CIO in a healthcare company.
From aiding clinical support in decision-making to enabling population health management, these areas of AI in healthcare could be best focused once there is stringent data governance and ethics in place. As researchers continue to study the limits of AI in healthcare, we should aim to take care of the safety and accountability aspects quicker than ever. How a patient feels about letting AI and Machine Learning-based programs take the control of their diagnosis is yet to be fully understood. We would wait for the clinical mandate of letting this happen in 2020.
For now, the human-machine interaction has never been this exciting.