Radiology As A Branch: Is AI A Threat?

Artificial intelligence in radiography is not a new thing. Many years ago it was predicted that with the use of AI, imaging would make a huge advancement. 

Radiology is an area of medicine that uses radiation to take imaging of the human body, like X-rays, CT scans, MRI scans etc. This imaging detects anomalies in the human body. 

The person trained to go through these images is called a radiologist. The radiologist in their entire career has to go through millions of imagining to become more accurate in their findings. It involves a lot of scrutiny and attention to detail when generating medical reports. 

However, due to the advancement of machine learning algorithms in radiology, AI in medical imaging has become faster, and more accurate than the radiologists.  

Here are a few benefits of artificial intelligence in radiology:

1. Accurate reports:

The use of artificial intelligence methods can provide accurate reports. Deep learning algorithms have reached such a point that it can detect accurate anomalies in the imaging with great calculation within minutes.  

Not only that it also provides the reports much faster than a human behind the screen studying the reports. 

2. Quicker results:

This is one of the most interesting things ever to happen in the AI medical space. It has been said that reports are usually late by medical practitioners. 

First, the medical imaging is done, then the imaging is processed and the radiologist then studies and analyses the imaging, and writes a detailed report on it. 

A radiologist has to do all this, but when the count of patients is high, it can cause a lot of stress on the radiologist which can increase the chance of errors in the report. 

3. Enter AI.

Artificial intelligence methods can help in reducing the stress of the radiologist as it calculates the imaging accurately, and sends timely reports. Radiologists can work with AI to generate an advanced set of reports. 

Let’s talk about the drawbacks:

1. The threat of data breach:

AI algorithms in medicine need to be trained to give proper reports and make faster decisions. This can be done using the data of the preexisting patients. The data of patients has to be fed to the machine learning algorithms so they can make calculations around it, and get trained. 

This can prove to be a huge risk, as the data of many people is under threat.  

There are chances of data loss and theft of patients' information which can be used to extort money from patients. 

2. Possibility of unemployment:

As AI gets more and more advanced with time, it can be trained efficiently to make quick decisions within minutes. It can be trained to generate accurate reports faster than the radiologist which can cause unemployment of radiologists. 

Many routine tasks of radiologists such as report generation and image segmentation are already done by AI, the day is not far when there might be huge unemployment of radiologists in the medical field.  

But that day is yet to come. Machine learning algorithms are still getting trained, and if you’re still employed, then congratulations. Working as a radiologist is tough, but all you need during these tough hours is a good pair of doctors' scrubs, a lab coat, and under scrubs. If you’re planning to buy these things then you can buy them at Knya.  

Knya is the ultimate destination to buy medical apparel online. Here you can buy men's lab coats, women's lab coats, and men's scrub and women's scrub, at affordable prices. 

Doctor Diagnostics: Dr. Ayush's Journey in Radiology

Watch the following video to learn about the life and career of a radiologist as Dr. Ayush reveals his personal journey and professional experiences:

 

FAQ's

Are there any limitations or challenges in implementing AI in radiology?

There are many limitations and challenges concerning radiology. Many things must be taken into consideration before diving into the AI revolution full-fledged. Challenges arise due to the use of data on the patients, can be data theft. There is also a possibility of unemployment of radiologists as many routine tasks can now be done by the AI like the generation of reports, image segmentation and analysis.

How does AI improve the accuracy and speed of radiological diagnoses?

Artificial intelligence’s use in medical radiology can improve the speed and accuracy of radiological diagnosis as the algorithm is fed datasets of thousands or millions of patients. When the data is fed to artificial intelligence, it gives intelligent solutions to radiological diagnoses. It is said to be much faster than the radiologist. The radiologist has to train himself/herself to see thousands of imaging before getting good at medical radiology, artificial intelligence can train itself after looking at millions of medical imaging in minutes. However, nothing beats the intelligence and expertise of a human radiologist.

What are the ethical considerations surrounding AI's use in medical radiology?

The use of AI in radiology is a bit critical. As machine learning has to learn to give accurate data and reports to the patient, the AI has to be fed the medical and private information of patients to train the machine learning algorithm. When this can happen, there can be a threat of data breach of patients by the AI tool. Ethical considerations regarding data protection must be taken before training the algorithm to give accurate information.