In the past, data analysts would work through the entire process of sifting through masses of data, breaking down its written layers into a format that could be understood by a computer. When completing this task, computer scientists discovered that the task at hand was too tasking and time-consuming to be completed by manual power. Here lead to the partnership of Big Data and AI.
The Collaboration Of AI and Big Data
By accumulating data from a range of sources, Big Data and AI are able to collate an extensive knowledge base that will enable the technology to make predictions about a consumer based solely on each of their daily movements and choices. Because of this amazing ability to work with large scale data, artificial intelligence was the best companion, to pair alongside the growing scale of data, now referred to as big data.
With the use of machine learning, each piece of data collated and stored is now being used to generate new business ideas and recommend key steps that should be taken. Within the radiology industry, this is something that is massively impactful, allowing the industry to use the powerful technology to improve higher qualities of work and reach greater heights.
The Radiology Industry
Radiology is the term used in the industry whose sole purpose is to create medical images through the use of a multi-screen workstation. These images can aid in the diagnosis, and chosen treatment for diseases found in both humans and animals.
The process is completed by a team of professionals who ensure each step is taken with the most seriousness, using techniques and methods that have proven to be very beneficial within past treatments.
Through the use of an MRI scanner, producing quality, digital images across multiple sections of the body with ease and speed.
Now, however, with the addition of artificial intelligence, the radiology industry has never been more trustworthy.
The Development Of Radiomics
There have been many occasions where the innovation of artificial intelligence can bring masses of potential to the healthcare sector. Particularly within areas of radiology and pathology, due to their jobs requiring the production of digital imagery.
Big Data and AI were tested to work within this industry. This is achieved by first examining previously scanned images from past patients, with the hopes that it will generate new rules and steps for producing these scans in the future. From here, the development of radiomics was produced. The potential of this technology can offer masses of opportunities to the healthcare sector, aiding in diagnosis, treatment and the overall well being of all patients as a nation.
A recent study conducted at Stanford University suggests that AI could help radiologists improve within various sectors of their job roles. For example, the production and analysis of mammograms, which will ultimately aid in the decrease of false positives and negatives being produced from research, that can easily occur through human error.
As well as this key benefit, it has been said that Big Data and AI have allowed more accurate predictions to be collated, from completing a brain MRI scan through the use of machine learning. In fact, it has actually been stated the accuracy is at a 90-95% height, a far more trusting amount for both doctors and patients.
With the ability of technology to work countless hours, tirelessly, it allows space for the radiology clinicians to make inquisitive decisions, with the help of artificial intelligence aid.
Replacement Of Radiologists
It has been predicted that through the inflation of artificial intelligence within the radiology sector, the amount of those who are actually needed may be hit with a decline. It is said that radiologists may become the manager of the technology, rather than the on hand, doctor for diagnoses.
Radiologists to an extent will not be extinct, with those in highest positions likely being able to keep their role within the healthcare industry. The power and ability of technology are slowly showing that this is the best way to ensure that patients receive the highest quality of treatment, hopefully leading to a higher success rate within hospitals up and down the country.
The diagnostic imagery is said to experience many positives from the use of artificial intelligence. Most particularly in the area of improving the accuracy of each step of the procedure. This added accuracy can result in each step becoming more time-efficient too, a crucial feature when it comes to the entire healthcare industry.
It is not only within the physical treatment sector where artificial intelligence can be useful. In fact, machine learning can be used as a form commonly known as ‘non-interpretive AI’.
Non-interpretive AI is the use of software that aids the industry to complete the operational tasks. For example finance management, promoting workflow efficiency by integrating tasks, calls, emails and improving quality.
Within the radiology industry, artificial intelligence has already been successful with the process of identifying patterns through images, noticing similar pictured problems and analysing them. This form of AI is used mostly within oncology, in order for doctors to be able to focus on the history and development of a tumour. Now, however, it has been suggested that there are new tools that can pinpoint the features that make for a better prognosis and problem indicator.
This is a feature that many doctors would agree is something they would not be able to predict or notice themselves, and through the use of Big Data and AI analysis, this is now able to be completed with efficiency that can only get better.
Advancing Interventional Radiology
Interventional radiology refers to the use of much less invasive procedures. For example, the use of X-rays or ultrasound, before the patient will continue onto the further treatments that may need a higher skilled doctor. The use of Interventional Radiology is done in circumstances where it is a quicker and safer alternative to other available processes. This leads to better outcomes for patients, and also a more efficient work rate.
The demands for this being available in all hospitals is always growing, so it is clear more doctors are needing to be trained within this sector, in order to offer it to more patients.
Big Data and AI can help with this. Through coaching a large amount of people at one time, to the possibility of artificial intelligence taking this job role itself, to being able to perform scans on patients if the doctors are unavailable.
Artificial intelligence is a recent development in technology here to change the way in which various industries work forever. While it may still be in the process of working its way further into the radiology industry, it has already made a change improving the industry for the better.
From being able to compute to create tedious and mundane tasks that would usually be done on the daily by someone at a desk, to being able to diagnose and predict patterns with the confidence of accuracy at hand. Artificial Intelligence is also able to turn the healthcare industry into a place where patients are treated with the most success, allowing them to leave confident that they were in the right hands.
It is unclear as to whether the features above are certain to be used within radiology within the next few years, but from analysis of the way the AI development is already progressing, there is no doubt that all of these things will not happen, as well as much more exciting technology progresses.
Sydney Tierney; just recently finished her studies; is working her way into the world of content writing as a digital marketing assistant. She writes for clients that specialise in workstations, Strategic Sourcing and Google Shopping Specialists.