Artificial intelligence may be used to accomplish a wide range of functions, including problem-solving, among many others. The application of artificial intelligence in specialized areas, such as healthcare, is, on the other hand, less well known.
The healthcare business is changing as artificial intelligence, and machine learning becomes more ubiquitous in technology. Insider Intelligence’s investment in artificial intelligence in medicine would expand at an annualized pace of 48 percent between 2017 and 2023.
What is Artificial Intelligence in Healthcare?
Physicians and hospital staff could benefit from data-driven clinical decision support (CDS) provided by machine learning, leading to a rise in revenue. Using algorithms and data, deep learning, a subset of AI that identifies patterns, can provide automated insights to healthcare professionals.
Artificial Intelligence (AI) in Healthcare: Advantages
Access to Healthcare
Healthcare is a significant issue in many developing and developing countries. Technology can address these issues at a fraction of the cost of building traditional infrastructure. Digital healthcare ecosystems can benefit from AI innovations by becoming more intelligent and efficient. It can be used to detect disease symptoms and prescribe medication remotely. AI technology is expected to impact healthcare diagnostics with each passing year significantly. Apps for healthcare can help the poorest people get better access to medical advice.
Improved patient experience:
- Healthcare facilities are overcrowded.
- Reports are piling up.
- Insurance is a source of constant confusion, contributing to a chaotic daily experience for patients.
By quickly scanning through data, getting reports ready, and allowing patients to know precisely where to go and who to contact via mobile devices, AI has emerged as a hero in these situations. As remote consulting becomes more common, AI serves as the backbone of some of the most advanced digital solutions, enabling accurate updates on timings and availability of reports and appointments, among other things.
AI-assisted surgery
Surgical robotics is one of the most cutting-edge AI applications in healthcare. With the advancement of AI robotics, surgical systems that can perform even the tiniest of movements have been developed. As a result, the average wait time for procedures and the risk, blood loss, complications, and possible side effects of these procedures can be reduced by using these systems.
Surgical operations can also benefit from machine learning. It can help healthcare professionals and surgeons access real-time information and intelligent insights about a patient’s current state. They use this AI-backed information to make quick and intelligent decisions before, during, and after procedures to ensure the best possible outcomes.
Insights into clinical health data
There is currently a lot of clinical data being generated in healthcare facilities, and clinicians are struggling to keep up. Without a proper mechanism for processing raw data, an ever-increasing amount of data is useless. Smart AI algorithms can help mitigate this by analysing data and providing insights. Artificial intelligence can pick up on otherwise invisible patterns, unlike the human eye. It’s up to both patients and doctors to make the best healthcare decisions based on this information. AI, for example, can not only keep track of blood glucose levels, but it can also determine whether the trend is upward or downward and provide suggestions for immediate action.
Management of the health of the general population
Using artificial intelligence (AI), healthcare organizations can collect and analyse patient health data to identify and prevent risks, close preventive care gaps, and better understand how clinical, genetic, behavioural, and environmental factors affect a population. It is possible to get a comprehensive picture of a patient’s health by using diagnostic information, examination results, and unstructured narrative data. Data points gathered at the population level can be compared to population-level patterns using AI-driven tools to identify early disease risks.
Predictive analytics
With this information, predictive analytics can be used to gain insight into the general population. It is then possible to use these findings to categorize people into risk groups according to genetic and phenotypic factors, along with behavioural drivers and social factors. Thanks to these findings, healthcare organizations can now provide more personalized, data-driven care while optimizing resource allocation and utilization, leading to better patient outcomes.
Reduction in cost
Frost & Sullivan estimates that artificial intelligence (AI) can improve healthcare outcomes by 30% to 40% while reducing treatment costs by 50%! Health care facilities will see a decrease in foot traffic due to increased precision and efficiency, which will reduce their workload. Patients who are at risk of re-admission can also be identified so that doctors can take steps to prevent them from being readmitted.
Conclusion:
Despite all the progress that AI has already made, it is still in its infancy in healthcare. In the coming years, new capabilities will be added to the technology due to ongoing research, resulting in even more significant breakthroughs in numerous industries. When it comes to healthcare, which is experiencing the most rapid transition to digital at the moment. AI and ML can make a significant impact on customer experience, create new digital lines of business, and reach research goals more quickly. All of which contribute to making the world a better and safer place for everyone to live in. There are digital native companies like Brainpool. It can help with figuring out where to start and how to formulate the right transformation strategy, but it can be difficult. To learn how AI and other cutting-edge technologies can benefit your healthcare or medical device company, don’t hesitate to get in touch with Brainpool.
