AI in Healthcare: Transforming the Practice of Medicine
One of the most significant contemporary developments in global healthcare is the use of artificial intelligence (AI) technologies in medicine. AI technology is enabling the development of new drugs, radical changes in the medical diagnostic process, and other improvements in the healthcare industry, as well as reducing healthcare costs.
What Is AI?
One of the first definitions of AI was suggested in the 1980s. Computer scientists, Feigenbaum and Barr defined AI as a branch of computer science that aims to develop intelligent computers with the qualities innate to the human mind. These comprise the capacity for learning, language comprehension, critical thinking, and problem-solving.
Today, the term “AI” refers to computer programs that use a set of algorithms and techniques to solve issues intellectually, just like a human. The main capabilities of AI are:
- Predicting various situations. The predictive ability of the machine algorithm is at a fairly high level. Relying on previously received and processed data, AI uses algorithms to recreate possible developments of events and situations.
- Evaluating the information and formulating a final assessment. In addition to predicting the development of a further situation, AI can give an estimate based on data, available information, and a possible outcome.
- Analyzing data and looking for hidden patterns. By observing many samples, AI may independently identify patterns in the data and draw attention to any underlying features.
Later, a variety of software programs and algorithms started to be referred to as AI. Its defining characteristic is the ability to address specific issues as a human would.
How Does AI Work in the Medical Field?
Today, a variety of medical technologies have been created using AI, and some of them are already in use in clinics worldwide.
The human body is the most complicated system in the world, and health technology provides access to it. We are learning new things about the human body using techniques like AI and machine learning to develop treatments that benefit patients and medical professionals.
Modern healthcare systems are revolutionizing clinical decision-making, personalizing care, and enhancing outcomes with the use of artificial intelligence, sensor technology, and data analysis.
Robotic surgery and the world’s smallest pacemaker are just two examples of the interplay between healthcare and artificial intelligence. The latest developments in medical technology help doctors detect diseases at an early stage and initiate gentle therapy. Let’s explore some other examples of how AI is transforming medical practice.
AI-based Prediction of a Decline in Blood Pressure
The algorithm was created using medical machine-learning techniques. The researchers examined data from more than 1,300 patients whose blood pressure was monitored throughout surgery. The observation lasted over 546 thousand minutes in total. As a result, AI-assisted in developing a hypotension prediction system.
The researchers retested the method with 204 additional cases. The AI could accurately predict a rapid drop in blood pressure: 84% of cases within 15 minutes, 84% of cases within 10 minutes, and 87% of cases within 5 minutes in advance. The researchers believe the method can reduce the risk of complications during surgery.
Skin Cancer Awareness
The use of AI in healthcare has led to significant achievements in early cancer early detection. Scientists from the United States, France, and Germany experimented in 2018 and trained neural networks to recognize photos to detect skin cancer.
More than 100,000 photographs of life-threatening melanomas and normal moles were sent into the system. Professional dermatologists then viewed the same images and attempted to detect malignancy based on them.
The machine performed the work more effectively than the experts. It properly identified malignant tumours in 95% of the cases, but humans only displayed the result in 86% of the cases.
AI in Ultrasound Examination of Pregnant Women
Some UK institutions are already utilizing a novel technique to screen the fetus for abnormalities that are challenging or impossible to find using conventional methods. The AI-based system has more than 350 thousand photos of embryos with different variations.
Based on the information in the database for previous patients, the technology known as ScanNav can provide the doctor with a lot of helpful information on the diseases of the unborn child. ScanNav is currently only used in obstetrics and is still in test mode, but in the future, it may become much more common and will be especially helpful for nations that have a severe physician shortage.
Why Do We Need AI in Medicine?
When it comes to using AI in medicine, its primary advantage is that it will improve the precision of illness diagnosis. While a neural network with access to a vast amount of data, cutting-edge scientific literature, and millions of case histories will be able to classify any case quickly, correlate it with similar problems in other patients, and suggest a treatment plan, it may be difficult for a doctor to identify a specific issue in the human body quickly.
AI is now unable to tackle complicated medical issues. It will not create technology in the future that can scan the human body in seconds, diagnose any problem, and recommend the best course of action. However, the current potential is still quite intriguing for physicians, patients, and clinics.
