AI Healthcare Strategies
There are a number of uses for artificial intelligence, and in particular the field of AI healthcare, to improve the quality of healthcare. The first use for this technology came from computer simulation of the human gastrointestinal system. Researchers at Penn State University managed to reproduce the digestive processes of a human being by means of an artificial intelligence program. This research gave insights into the complexities of the human gastrointestinal tract, which can deter human doctors from prescribing the right drugs. This research paved the way for better simulations.
Healthcare is a growing industry with a large number of patients and doctors. Traditional computer algorithms have historically been used to analyze medical images, but these algorithms, while effective for some applications, are not well suited for all. For example, standard computer algorithms cannot identify breast cancer in women that have undergone mammograms. This problem led to the development of medical imaging systems that use machine vision to identify cancerous tissue. Another example is that standard algorithms cannot identify kidney stones in patients that are prescribed blood thinners.
Machine learning is a form of artificial intelligence, and it was first applied in the areas of education and manufacturing. Now, it has become crucial in many fields including healthcare. AI Healthcare will give healthcare providers the ability to make smart decisions about patient care based on multiple input data, deep knowledge of anatomy and physiology, as well as previous medical histories and current health conditions. The potential applications for AI Healthcare range from pre-natal care to cancer screenings to heart disease and much more.
One of the most popular applications is in the area of medication dosage adjustment. Drug companies rely heavily on drug calculations to ensure the correct amount of medication is given to patients suffering from a certain ailment or disease. However, a great portion of dosage calculations are done by hand. This traditional method of computing resulted in long periods of time spent computing the same information repeatedly. With the introduction of machine learning algorithms, medication dosage adjustments can be done accurately in just a few minutes instead of the several hours it would take with humans. Additionally, the accuracy of these algorithms is guaranteed to improve over time as the healthcare industry continues to collect and aggregate more patient data.
Another application of AI healthcare is payment processing. By using deep learning algorithms, pharmaceutical companies can identify payment errors much faster and more efficiently than an employee. Currently, it takes several days before the company receives its payment from the insurance company. Once the software is able to detect errors, it can quickly correct them and prevent further damage to the company’s reputation.
One other application is medical imaging. Until recently, it was necessary for healthcare workers to manually key in patient details into a computer, creating error-filled reports that could be very time-consuming. However, medical imaging programs such as digital x-ray machines and software to help reduce errors significantly. As more healthcare organizations adopt deep learning algorithms to process their patient data, they will become more efficient and save the healthcare industry money in the long run. Furthermore, the accuracy rate for machine learning algorithms has improved over time.
One more application of artificial intelligence is healthcare ehr. Electronic Health Record software is designed to allow doctors and other staff members to create accurate patient records with just a few clicks of the mouse. Rather than writing out paper records by hand, the ehr system allows patients to upload detailed information about themselves so that their records can be automatically stored and retrieved when needed. Currently, EHRs are being used in hospitals in the U.S., England, France and Spain, and are showing promising results. In addition, improvements in battery life for computers used to process the electronic health records are reducing the costs of maintaining the system overall.
AI healthcare may ultimately impact every healthcare organization in the country. Currently, the healthcare industry is largely composed of physicians, surgeons, nurses and technicians. However, as the cost of healthcare rises, more specialists will be required and that means increased training costs. AI technology can make the workforce more efficient and provide superior results in terms of care, while eliminating some of the current training requirements.