Technology advancements are moving fast, and real-world applications of artificial intelligence (AI) are becoming more prevalent and accessible every day. The opportunities for research and use of AI to improve our day-to-day lives are exciting and alluring to many, and we know AI is an area that will have a major impact on society in the near future. A Medical Spa, for instance, may need to employ advanced technology for aesthetic treatments as well as for the management and other official functions. They might need a platform that enables them to integrate all of their operations into one system for the most efficient and effective operations. In that regard, such clinics can take advantage of ERMs and CRM software to streamline their operations and handle patients like professionals.
Moreover, in the realm of human resources, AI can be helpful in recruitment. Companies can use AI tools to streamline the hiring process, from screening resumes to conducting assessments. These are just some of the ways AI is transforming various industries, making processes more efficient. Having said that, let’s dive into the future and examine some of the most interesting real-world applications of AI.
Healthcare Providers Outperform the Competition
Many news outlets and podcasts have extensively covered the impact of AI in Healthcare, and all the possible ways it can be integrated into the industry. AI has already been proven to identify patterns in speech patterns and preferences in order to better fit a caller into a network, but is it also capable of identifying the most efficient way to deliver a service? Doctors for America is a non-profit organisation that provides a broad range of healthcare services including physician training, telemedicine, research, and patient advocacy. Their AI platform, STATISTICA, allows providers to share their most efficient treatment and service delivery methods in order to ensure patients receive the best care possible, and in fact, reported that providers were able to cut down their use of expensive procedures by 30% and consequently saved over $20 million in four years.
I’m pretty sure some very intuitive AI bots are used to come up with those new casinos lists that have some great welcome bonuses for new players!
Saving Money on Critical Care Medicine
For patients who are at the highest risk for certain serious conditions, it’s critical they receive the best care. Instead of having a limited number of cardiologists treating patients, researchers have turned to artificial intelligence to create algorithms that can predict who would be a candidate for a procedure such as open heart surgery, instead of making such an invasive decision based on knowledge about a patient’s personal health history. The University of Maryland’s Perelman School of Medicine, in conjunction with the University of Utah and UC San Diego, took artificial intelligence to heart to improve healthcare by designing algorithms to identify what diseases patients with sickle cell trait were most at risk for. The research was published in the journal PLoS One and was conducted on 2,039 patient records in the United States. The best part of it is that these research papers and discussions on any critical cases can now be discussed on Sermo (https://www.sermo.com/) and other social networks meant for physicians. The medical professionals can share their knowledge and exchange insights to solve different challenging patient cases.
Recruitment for A-Fib-ridden Workers
What if we could use AI to select candidates that might be suffering from a serious heart condition? The problem with current screening methods is that they don’t provide a complete picture of a candidate’s health. It’s difficult for doctors to detect even the most serious diseases in the early stages, but a new software called Einstein GYPSY uses AI to scan scans and produce screening results for different heart conditions. It can be used to detect atrial fibrillation with 98% accuracy. A team at the UPMC Presbyterian Hospital in Pittsburgh tested it on 88 patients, and by correctly diagnosing cases, it saved seven lives. However, there’s still much more work to be done before it can be implemented on the public, which means many people will have to wait until other medical professionals (often overburdened) make the move to using it.
