The application of artificial intelligence in healthcare is being discussed and applied as much as in other industries. Since AI has already completed accurate tasks in the field of diagnosis, it is expected to play a key role in the field of medicine in the future. However, there are some challenges in training AI to examine a patient's condition over time and calculate treatment recommendations.
In an intensive care unit, many different pieces of data are collected around the clock. Patients are under constant medical monitoring. This is a conclusion that doctors draw based on observations based on these rules.
In most cases, they will understand the parameters that must be considered in order to provide optimal care in the ICU. Here, using a computer can do wonders as it can capture more parameters.
For example, splitting a large number of images into those that show tumors and those that don't show tumors, but rather about the progression over time, about what a certain patient may have experienced develop. Mathematically, this is something completely different. There is very little research on this in the medical community.
Here, the computer acts as an agent and can make independent decisions. The computer receives "rewards" only when the patient is healthy and "punishes" if the patient's condition worsens. Additionally, the computer was programmed to increase its virtual "rewards" by taking actions at the right time. As a result, large amounts of medical data can be used to automatically determine a strategy, often with a high success rate.
Understanding the potential of artificial intelligence in this context will be a game changer. For example, sepsis is one of the most common causes of death in critical care medicine and poses a huge challenge to physicians and hospitals because early detection and treatment are critical to patient survival.
To date, there have been few medical breakthroughs in this area, making the search for new treatments and approaches even more urgent. For this reason, it is particularly interesting to investigate the extent to which artificial intelligence can contribute to improving healthcare.
Due to the use of artificial intelligence strategies rather than human decision-making, the cure rate is quite high, so it can be said that artificial intelligence has surpassed human capabilities. For example, the cure rate for 90-day mortality jumped from 3% to about 88%, according to their study.
Although artificial intelligence has the possibility of high accuracy, we cannot rely entirely on computers. Instead, AI may be able to operate as an add-on device at the bedside. Healthcare professionals can refer to this information to compare their assessments with AI recommendations and observations.
The first question that comes to mind may be that mistakes made by artificial intelligence need to be held accountable. But there is also a reverse problem. What if the AI makes the right decision, but the human chooses a different treatment, and the patient is harmed as a result?” This raises questions, such as whether doctors can be accused of being distrustful because of their extensive data and experience. Artificial Intelligence.
According to research projects, artificial intelligence can already be successfully used in clinical practice with today's technology; discussion of social frameworks and clear legal rules is inevitable.
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