Pros and Cons: Artificial Intelligence in Patients Diagnosing


Pros and Cons: Artificial Intelligence in Patients Diagnosing
Pros and Cons: Artificial Intelligence in Patients Diagnosing
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Implementing AI algorithms to custom healthcare solutions today is very common. But are we sure that they help us, especially in such an extremely important area as healthcare? Is this just a crazy burst of machine evolution, or does it help us in the diagnosis of disease? There are two sides to the coin, and we discover them in this article.

Let’s start with the positive, how artificial intelligence helps to detect diseases in the early stages, and review some examples.

Pros

  1. Easier access to healthcare systems

As a rule, underdeveloped countries have little or no access to healthcare facilities and systems and have a hard time keeping up with the rapidly developing technologies in developed countries. Unfortunately, mortality rates are also higher in these countries.

According to WHO statistics, limited or inaccessible healthcare is the reason for the life expectancy gap between the world’s richest and poorest countries.

Utilizing artificial intelligence in underdeveloped countries will not only help reduce mortality but also have a digital and accessible healthcare software system that will facilitate patient diagnosis and treatment.

  1. Early disease detection

Developed AI custom software systems now use patient data to evaluate both past and current medical conditions. Medical experts may improve their diagnostic accuracy by comparing patient records. Millions of symptoms and diagnoses have been computed in the database of multiple mobile health applications. Perhaps more crucially, it may foretell future health problems that a person may face.

One example is Google’s Verily program, which may one day be able to foresee the start of heritable but not contagious diseases. Healthcare providers are better able to anticipate future hazards and take preventative measures with the help of such instruments. Similarly, predictive analysis has improved the quality of management in healthcare institutions.

  1. Better Patient Care
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Patients have a negative experience in healthcare facilities that are overcrowded and disorganized. With the aid of AI, patients may rapidly get the information they need, get the reports they need, and be routed to the right place to see the right doctor, all while avoiding the normal chaos that plagues healthcare facilities.

The 24/7 accessibility of AI technology for patients is another incomparable benefit. Babylon, a software that can function as a user-friendly side effects checker, is an amazing example of how artificial intelligence used in medicine may improve the patient’s experience. To deliver up-to-date, reliable medical advice, the custom software system queries the user, analyzes their responses, and then compares the results to a database of known symptoms and risk factors.

  1. Effective and innovative surgical aid

The use of AI in robotics has advanced significantly in recent years. The same holds for using ML in the operating room. Artificially intelligent surgical systems are available, capable of performing even the most delicate procedures with pinpoint precision. This allows us to do delicate procedures with little time spent in recovery and no need for unnecessary blood transfusions or pain medication. Similarly, recuperation times after surgery have decreased.

Before surgery, patients are treated with antibacterial nanorobots to remove any blood infections. The fact that surgeons have access to real-time AI-backed data on the patient’s current condition is perhaps the finest aspect. This has helped put patients at ease, particularly those anxious about undergoing surgery while under general anesthesia.

  1. Improved mental health and abilities

Medical professionals and patients alike may now benefit from robotic assistance. Paralyzed persons, for instance, may walk again with the aid of exoskeleton robots and need just little assistance from caregivers. In the same way, sensors in smart AI-backed prostheses allow them to be more responsive than conventional ones.

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Using machine learning, service robots may assist with routine duties and provide companionship to those who need it. Dedicated companion and conversational robots may monitor vitals including blood sugar, blood pressure, body temperature, and even administer medication. Robots with built-in analytical skills have been designed to aid depressed individuals. They may now assess a patient’s mood and provide upbeat advice to lift their spirits.

It’s all about the advantages. Let’s move on to the difficulties.

Cons

The Brookings Institute released a paper validating concerns about artificial intelligence in medical care. Several of them are noted below:

Mistakes and injury

AI systems are prone to mistakes, which may ultimately result in patient damage or other serious issues. For instance, a patient can take a medication that was incorrectly suggested by the AI system, raising extra concerns. The radiological scan that is run by AI might also miss the disease.

Their main worry is that mistakes with AI could have wide-reaching effects. One mistake might hurt several patients. No family member or friend will be happy to hear that a person they care about had a problem with the robot. AI skills are easier to criticize because of the custom software review system for patients, but they are harder to remember.

Privacy concerns

Privacy is a major concern regarding the acquisition of patient data. While safeguards exist to protect patient information, malicious hackers are actively attempting to gain access. If a behemoth like Google can have privacy and patient data issues, then nobody in AI should ignore privacy concerns.

Another privacy concern with AI is that it may make predictions about patients even if such information was never provided.

Unfairness and discrimination

AI is susceptible to partiality. Even the slightest indication of bias is always reflected in the outcomes. For example, when data from academic medical centers are incorporated into AI systems, it may be difficult for these systems to treat or benefit populations from areas other than academic medical centers. In the same way, using speech-recognition AI systems to transcribe notes may make the AI less effective if the person providing the training data is of a minority gender or race.

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Professional reorganization

If AI technology is fully implemented, the medical field may transform. Some academicians’ view that the pervasive use of artificial intelligence will diminish human knowledge and capability over time is gaining support. According to them, there may come a time when providers can effectively prevent AI mistakes or advance medical knowledge.

Negative diagnosis

We have already discussed the need for high-quality provided disease detection in this article. However, there is a significant danger of erroneous diagnosis if artificial intelligence systems are not administered with sufficient data from diverse backgrounds. Physicians only have enough experience with AI to identify an error if AI can be explained. In the event of a false diagnosis, accountability is questioned.

For example, is the doctor in control who relied on AI to make a decision accountable for the accident or mistake? Because of the deployment of AI, the healthcare industry may be confronted with many ethical dilemmas. However, it is crucial to recognize that medical and AI diagnoses contain an error margin. A global study on primary care errors revealed that 5 percent of all patients receive an incorrect diagnosis and that a third of all severe illnesses are misdiagnosed, resulting in damage.

Finally

So, we’re broken down the pros and cons that can be encountered when using artificial intelligence to avoid considering this article. Artificial intelligence does help in many ways, from disease detection to robotic intervention in surgery. But it’s also important to remember that there are certain risks, and there may be a mistake in the diagnosis, so everything should be checked carefully.


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nitin kumar