The Significant Impacts of Artificial Intelligence in Healthcare
As technology rapidly advances, so does the potential for artificial intelligence (AI) to significantly impact various industries, including healthcare. Artificial intelligence in healthcare has endless benefits that could impact the whole field, from diagnosing diseases to handling radiography.
Healthcare and AI are becoming closely tight together, and it’s easy to see why. The ability of artificial intelligence (AI) to differentiate between the healthy and sick in a healthcare setting is one of its greatest advantages over traditional analytics processes.
Learning algorithms will become more precise as they interact with training data, allowing patients to gain new insights into diagnoses, treatment methods, and outcomes.
There are a few elements when it comes to healthcare and AI, and we will discuss the most impactful in this post.
4 Impacts of Artificial Intelligence on Healthcare
AI Can Deeply Analyze Patients for Early Intervention
Artificial intelligence has the potential to change the landscape of healthcare as we know it. By integrating AI into major disease areas, we can enable predictive analytics for early intervention. This means that AI can help us to identify risk factors for diseases sooner, such as neurological, cardiovascular, and cancer illnesses, which are the major causes of death.
Artificial intelligence-based algorithms can detect genetic changes and abnormal protein interactions earlier than ever. Modern medical research also strives to use AI technology responsibly and ethically.
On the other hand, according to research by the Department of Stroke and Vascular Neurology at the University of Hong Kong, machine learning could detect a future stroke in a patient. The accuracy of this research was 70%, so it goes without saying that AI has a lot of potential in the industry.
Artificial Intelligence May Provide the Next Generation of Radiological Tools
The basis of machine learning is to extract particular patient data and health history to then use its algorithm and detect early problems. Among all the data collected, we can find physical exam results, drug prescriptions, important statistics, gene expressions, and several tests that the patient had done previously.
This is precisely why AI will soon become one of the most efficient tools in healthcare. The use of patient physical traits with a database of knowledge to deliver a more targeted result is referred to as supervised learning. And in the healthcare sector, supervised learning is the most popular type of Machine Learning. On the other hand, Modern Deep Learning has also been introduced to go deeper than conventional Machine Learning.
Deep Learning, unlike Machine Learning, takes the same data and feeds it into a computerized network, gathering more data before eventually delivering an easier output. This can be compared to a patient going to a doctor’s visit and asking, “What is this illness? I’ve never heard of it. Could you explain?” Also, when the diagnosis isn’t determined yet, all the information gathered will help doctors come to a conclusion more quickly.
Targeted Diagnostics Can be Produced by Using AI
Diagnostics can be much more accurate using AI, and there’s a good reason for that. Let’s take the example of lunch disease.
Occupational lung diseases are the most frequent cause of work-related illness in the United States, based on their prevalence and severity. Over a lengthy period of time, exposure to organic and inorganic chemicals and carcinogens at work may induce a number of lung diseases that might have long-term consequences.
New lung illnesses are constantly discovered, resulting in an increase in the number of workers who acquire lung sickness due to their job. Most persons exposed to pesticides at work experience only minor symptoms of lung illness during the first few years of employment.
A study by the Department of Radiology at the Massachusetts General Hospital in Boston revealed that AI could identify pulmonary nodules and, therefore, allows for a better diagnosis of lung cancer.
That’s not it; existing technologies such as MRI (Magnetic Resonance Imaging) and X-rays are proven, non-invasive methods to see the human body locally. However, in some cases, these aren’t enough, and more invasive procedures have to be processed, for instance, biopsies to sample tissue.
Machine Learning will gather enough data and evidence into the AI system, and eventually, it will allow experts to create a tool that will not need a tissue sample, hence, allowing the patients to avoid biopsies and other invasive procedures.
AI Will Decrease Healthcare Costs and Improve Efficiency in Healthcare Services
The COVID-19 pandemic created an urgent and massive need for medical care outside of hospitals, and, for this reason, there was a significant increase in telehealth services. So much that, according to a report by McKinsey, the number of people in the United States using telehealth services rather than traditional medical care skyrocketed from 11% to 46%.
This resulted in a remarkable change in the industry’s economy as the total revenues increased from $3 billion to over $250 billion.
This tells us that our system lacks efficient tools in case of emergency and is not in any case affordable. And this is where Artificial Intelligence comes in.
AI is being employed on a broader scale for serious and extreme diseases, but telehealth solutions are being used at home to assist in lowering hospital admissions. Telehealth systems allow various data points to be collected, recorded and analyzed in the same way that a larger AI system might.
And AI makes a monitoring system that allows for real-time remote patient care and monitoring. Overall, connected healthcare also implies enhanced access, more efficient and effective use of health resources, and more affordable service for patients.
Although it is still in its early developmental stages, AI has already begun to impact the healthcare industry in profound ways. From aiding doctors with diagnoses to helping patients manage their own health, AI is proving itself to be a valuable asset to healthcare professionals and patients.
As this technology continues to evolve, we can only expect these impacts to grow more significantly. How will AI alter the future of healthcare?