Artificial intelligence is a field of computer science that focuses on developing human-like intelligence in machines. It enables machines to process data, learn behaviors and patterns thus be able to offer predictions. Advancements in technology have made it possible for machines to be intelligent like human beings and even surpass the human brain capacity. A machine can now use a human being’s profile to log in on a site like vegas casino and place bets.
Within the healthcare industry, machines have been taught how to analyze patient symptoms and come up with diagnoses similar to what a human doctor would do. However, it is more efficient, accurate, cheaper and faster.
Artificial Intelligence in Various Branches of Medicine
Artificial intelligence is transforming medical fields like oncology, cardiology, dermatology, and more, enhancing diagnostic accuracy and treatment efficacy/ Sp let`s look at it closer.
- Oncology: machine learning has advanced the ability to identify underlying cancer symptoms through the use of primary data such as X-ray images. This assists the doctors detect the cancerous cells faster thus allowing for early treatment.
- Cardiology: robotics can be used to interpret the heart’s electrical signals hence allowing for early detection of any anomalies. There are options of devices you can wear such as smart watches that would monitor your heart rate and rhythm and send data that is analyzed by advanced machine learning. Once anomalies are discovered there can be preventive measures put in place to ensure a cardiac event does not occur.
- Dermatology: it helps with analyses of skin lesions to ascertain what caused them. Should they be cancerous, then the machine can quickly ascertain the same allowing the dermatologist to recommend appropriate treatment.
- Ophthalmology: the machines can analyze data in the form of eye images to ascertain whether there are any underlying conditions. It can thus be treated quickly and save the patient’s eyesight.
- Radiology: it can be used to read images like CT scans hence making diagnoses that can lead to faster treatment for the patients.
- Gastroenterology: robotics has been applied in the identification of abnormal gut tissue. Though research in the area is still new and more needs to be done, it is promising that soon machines will be able to provide accurate results better than any endoscopists.
- Infectious disease: there has been increased use of artificial intelligence in diagnosing some communicable illnesses like hepatitis A and B, and tuberculosis among others. It has shown great promise in improving the rate of determining the underlying problem enabling doctors to react quickly to prevent the spreading of the epidemic.
- Pathology: when data from microscopic swabs is fed to these machines, they can analyze it and give predictions on the presence of various diseases. Studies show that the use of both human knowledge and machine learning improves the accuracy of pathology thus offering better results on patients’ status.
- Neurology: this deeper learning has been used to better understand Alzheimer’s disease. By using MRI data from various patients, machines have been programmed to interpret it and offer valid predictions that can advance future learning on the topic.
Pros of Using Artificial Intelligence in Healthcare
There are several pros of using AI in healthcare that are revolutionizing healthcare by improving outcomes, efficiency, and patient care.
- Accuracy: the results from the machine are accurate and devoid of human error. They can thus be authoritatively used to recommend treatment.
- Fast: robotics allows for huge sets of data to be quickly analyzed and interpreted. Unlike a human being who takes a long time to reach conclusions.
- Offers assistance to human doctors: it acts as an aide to the human being who might not be able to access symptoms as fast or accurately. With the two working together, you get the best of both worlds.
- Less costly: through the use of this advanced learning, the underlying disease is ascertained easily and you do not need a multitude of tests to know what is ailing you. This saves on costs you would incur.
- Pattern recognition: it is easier for machines to recognize patterns occurring in a patient’s medical data than a human would. This enables the identification of personalized options for treatment best suited to you.
Cons of Machine Learning
With great benefits of using AI we also should mention that there are several cons or challenges associated with machine learning in healthcare:
- Over-reliance on it: the danger of developing this mode of science is that the role of human doctors could get drastically diminished leading to a scenario where the machines have the most control over your health care.
- Data privacy: the issue of data is an emerging problem that ought to be seriously considered in this new era of learning. This whole sector is pegged on access to patient data which comprises sensitive information. Appropriate rules should be put in place to safeguard patients from being exploited.
- Ethical issues: the problem is who takes responsibility for any wrongdoing that may occur. The machines do not have a conscience so have no indication of right and wrong. All they do is process information and give out a report but who is to be held accountable for that report?
- Job loss: as more advancements in technology take place, there is bound to be obsolescence in some job categories. So what is to happen to those who have the requisite education and skills that are now performed by machines?
Granted, the developments in technology have greatly impacted the healthcare industry and brought about significant improvements. However, caution must be had in ensuring that the human role is not completely diminished. After all, when you are sick, you always appreciate the sympathetic smile from your doctor that a machine cannot give you.
