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In the modern world we are seeing more and more ways that technology is impacting different aspects of our lives, and health care is no different. The growing use of Artificial Intelligence in digital healthcare brings several benefits to the sector, many of which will change the way we treat patients. Take a look below at some of biggest changes that AI can have on the medical field and our healthcare.
Recent studies show that over 12 million adults in the United States who seek outpatient medical care receive a misdiagnosis, which is around 1 in every 20 patients. The misdiagnosis could lead to drastic consequences for the patient, from both a physical and financial standpoint.
The use of artificial intelligence allows us to considerably increase the chances of an accurate diagnosis. One example of this is through the use of image recognition for cancer detection. AI can accurately detect and diagnose colorectal cancer by analysing thousands of images with the diagnosis and running them through a machine learning program to help accurately detect scans suffering from the same disease. The program recognises which images are suffering from the disease and lead the patient to a quicker diagnosis.
Another use of AI in disease diagnosis is through the use of Medical Learning Classifiers (MLC’s). Over decades of treating the health of millions of patients, there is a mass of Electronic Health Records documenting the different conditions and discoveries. Using these classifiers, AI allows for us to quickly scan these records in search of previous cases with similar symptoms.
This will allow physicians to directly compare current cases to previous conditions and therefore increase the likelihood of an accurate diagnosis.
Data-processing is a key area of healthcare, and the management of Electronic Healthcare Records (EHR) can become much more efficient with the use of AI. As time goes on, more and more information is being collected on these records from patients, which can cause delays for physicians when carrying out clinical data review.
Using AI technology, a system can now be created to organise patient health records and improve data retrieval with a faster and more accurate process. A study carried out by Stanford University used a pool of selected physicians to compare the data retrieval using two methods: an AI-optimised patient record and a standard non-AI-optimised patient record.
Overall, the vast majority of physicians preferred the AI record review due to the time taken to extract relevant patient data being decreased without compromising the level of accuracy. This integration of artificial intelligence with the healthcare system can therefore be used to provide patient care that is better, faster, and more efficient.
The practice of telemedicine and the distribution of health services through electronic information has increased in regularity over the last few years, and factors such as the COVID-19 pandemic have only increased its use and importance in modern day healthcare. Patients can now be monitored and treated remotely from the comfort of their own home, which is especially helpful for those with limited mobility.
Artificial intelligence can help assist remote treatment through the use of sensors and other wearable devices that monitor the condition of the patient. These devices can measure the standard readings of a patient, and can use that as a base to detect any abnormalities in their condition without the arranging of an appointment. This is especially useful for elderly patient who may live alone as they can still be monitored on a regular basis.
Whilst there are many benefits from integrating AI into our healthcare system, there are still some ethical concerns surrounding this technology.
As illustrated throughout, a lot of the benefits of AI come as a result of mass data collection. This may cause some privacy concerns with many patients not being comfortable with sharing private information, especially relating to their health. This, along with the rapid increase in technology, also means it may be difficult for patients to be aware of what information is being shared. This grey area of AI is therefore subject to some concern.
Whilst the benefits of AI include the increase in speed and productivity, this will as a result bypass certain roles in the industry and therefore cause some employees to become redundant. With a lot of the uses for Ai surrounding data collection and record keeping, there may be less use for human to operate certain jobs when there is already technology that can do it in a faster, more effective manner, and without the additional costs of a salary.
Artificial Intelligence is at its most effective when it is reliant on a larger data set to extract information from. A concern would be that several demographics that are historically underrepresented would be absent from this data and could cause an unwanted bias. If the data being used is prejudiced in favour of a particular demographic, then this could have severe consequences such as inaccurate diagnoses for minority demographics who may require a different set of treatment to the overrepresented demographic. It would be important to bear this in mind when using AI data sets to determine treatment for patients if such an integration is to become commonplace.
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