Artificial Intelligence, or AI, is bringing the world on its toes. AI is a collection of advanced technologies that include machine learning, deep learning, and neural networks. AI technologies are revolutionizing the way all industries work but the modern healthcare sector is showing a paradigm shift in the way patients are treated and medicines are discovered.
The popularity of AI technologies in the medical field can be measured by the fact that the market value of AI in the healthcare industry is expected to reach $6.6 billion by 2021. A recent report by Frost and Sullivan consulting firm, it was found that AI can cut the health treatment costs by half. This revolutionary technology is driving innovations in patient care, drug research, treatment, surgical procedures, health data management, and other clinical operations. Let’s check out in detail how does AI improving healthcare.
Artificial Intelligence has the ability to mimic a human’s cognitive functions and get machines to perform tasks with human-like problem-solving skills. In the healthcare industry, AI can provide doctors, researchers, physicians, and healthcare organizations with data-driven clinical decision support and automated insights.
The first application of AI was seen in the form of Electronic Health Records. But it wasn’t a smooth transition for medical facilities as endless documentation resulted in errors, security issues, and user burnout. With the advancement in the machine learning algorithms and deep learning, medical professionals can now save electronic health records easily and determine patterns for allergies, treatment, emergency care, and even send notifications to patients for overdue lab tests. AI has evolved and so are its applications in the health care sector.
AI applications in healthcare are centered around three important things: 1) digitization, 2) prediction, and 3) diagnostics. Let’s explore the latest uses of AI technologies in the medical field:
In response to the recent COVID-19 outbreak, the scientific community around the world are working together to understand the characteristics of the virus that causes coronavirus and discover vaccination to prevent future cases of COVID-19. Deepmind, a UK-based artificial intelligence company, has utilized its AlphaFold algorithm to predict the protein structures associated with SARS-CoV-2, which causes COVID-19. Here is the three-dimensional protein structure. (Image courtesy: Deepmind)
By understanding the protein structure of a virus, structural biologists and virologists can work together to create medicines that can stop them from multiplying in the human body or kill them.
Modern AI-based drug design software can learn the important features and characteristics of known drugs and create new molecules in a few minutes with the desired properties, thus saving lots of time and effort. Charles River, a contract research organization, is working on a project in which it is using AI to predict protein target binding sites for a large number of chemical compounds.
Robotic surgery has made it possible for doctors to operate patients with much more precision, flexibility, and control. A surgeon controls the arm of a robot through a computer and the small tools attached to the robotic arm. AI opens more doors of opportunities in the field of robot-assisted surgeries. AI technologies collect data related to surgical procedures and determine patterns to improve practices and accuracy. Machine learning could help surgeons view data, videos, simulations, and real-time interactions while performing robotic surgery on a particular individual.
Robots aren’t just assisting in surgery, they are making a big impact in other areas of medicine. Today, robots are being used in hospitals to disinfect patient rooms and transport specimens to labs, meals, and other items. Humanoids are bring used to provide personal care and training to patients.
Around 90 percent of all healthcare data comes from imaging technologies but if they are not analyzed properly, they may go in vain. Applying artificial intelligence to diagnostics can make tests more automated, accurate and faster, thus saving time and eliminating human error. Here are the AI applications in medical diagnostics:
• AI-chatbots with speech recognition can talk to patients and identify their symptoms and suggest an appropriate course of action.
• Facial recognition software is being used to detect facial phenotypes associated with rare diseases.
• Deep learning algorithms can study oncology reports and recognize cancerous tissues at an early stage.
• When AI algorithms are combined with the manual observation of pathology samples under a microscope by a trained physician, we can improve both speed and accuracy.
A recent survey by Pegasystems, it was found that 42% of patients and business decision-makers in the healthcare industry are comfortable in using AI systems. When it comes to patient engagement, AI can play a significant role in improving personalized care provided to them and their satisfaction level. AI tools used in the healthcare facility can provide a holistic view of an individual patient, anticipate his or her needs, and provide faster outcomes. AI-based virtual nurses can provide patients with next-best courses to take, personalized to their diagnosis and treatment procedure.
As we mentioned earlier, electronic health records were one of the first use cases of Artificial Intelligence. But today patient data management has become advanced with the development of deep learning algorithms and neural networks. AI-powered data management systems can analyze vast amounts of data and draw meaningful predictions before time. Here is how some companies are making use of AI in the patient data management.
• Tempus is using AI to analyze clinical and molecular data and determine personalized healthcare treatments.
• Proscia is a digital pathology platform that uses AI in cancer discovery and treatment.
• IBM’s Watson is using hospital and patient data to optimize the efficiency of healthcare professionals and improve treatments.
• Google’s DeepMind Health AI software is now being used in many hospitals for faster diagnoses of diseases and moving patients to the treatment stage more efficiently.
30% of healthcare costs are associated with administrative works. If we automate repetitive tasks using AI robots, healthcare facilities can save at least 20% of these admin expenses. Integrating AI into the healthcare ecosystem helps to automate tasks and analyze patient data to deliver better care faster, at a lower cost. AI is being used in the form of AI-chatbots and virtual nursing assistants that help to provide direct patient solutions and reduce demand on primary healthcare providers. Accenture estimated that virtual nursing assistants could help the U.S. healthcare industry to cut as much as $20 billion in costs.Accenture also revealed that top AI applications in healthcare could save $150 billion annually by 2026.
Conclusion
AI is here to stay. It is growing and expanding. It will not replace doctors but will revolutionize health care services and products. A lot of progress has already been made in AI healthcare services. Healthcare organizations need to accept AI technologies for streamlining administrative functions, providing better patient care, faster drug development, and improving proactive and preventive services.
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