Not all heroes wear capes, some come with algorithms, technology and a whole lot of artificial intelligence. Why do I make a claim as such you ask? AI is completely redefining the when, what, where and how of the way people are accessing healthcare. It seems to be bridging the gap between the haves and the have-nots. It is making high-quality medical care accessible for all. Trained healthcare professionals and physical clinics may have cost you a fortune earlier, but not anymore.
The gargantuan role that technology has been playing in medical care for the past two decades or so has been documented, praised, condemned, and experimented on, limitlessly. From facilitating early diagnosis of various medical conditions to enabling personalised treatment to abet the advancement of radiology, technology has seeped into all domains. At the centre of such latest evolutions is the use of AI in medical imaging, especially in telemedicine (provision of remote clinical services via real-time two-way communication between the patient and the healthcare provider).
Telemedicine is a branch of medicine that has received praise for enabling remote healthcare facilities. The main premise of it is technology where the doctor-patient relationship is built on exchanging medical information from one location to another through telecommunications technology. In simple, it extends the reach of medical care which is a plus point in itself. But what makes it indispensable is the use of AI as one of its main infrastructures. Especially AI in medical imaging. This is serving as a technological driver that disrupts under-served regions in a country by providing access to good medical care sans geographical constraints.
The role of AI is highlighted in medical imaging because one of the concerns that telemedicine was troubled by was the interpretation of medical images. This no longer would be an issue. For example, a patient who resides in a remote area can have their X-ray taken locally and transfer the images to their radiologist through AI. In addition, since their data is now stored electronically, drawing from that data for a better diagnosis will be a walk in the park. Not only is this effective, but this could eventually democratise healthcare by preventing high-quality healthcare from being gatekept.
Despite all its plus points, AI is not without its caveats, especially ones that involve data privacy and security. However, what recent trends demonstrate is that the advantages of AI surpass the disadvantages of it. If these cons are further diminished with apt regulation, AI could carry the world of medical care on its shoulders.
How is A.I. making headway in Medical Imaging
Since we’ve got a grasp of how medical imaging is making the world of medical care a more inclusive place to live in, let us look at some of its latest developments.
To translate medical imaging into layman’s terms, it is a branch of medicine that uses various technologies to create visual representations of the internal structures and functions of the human body. The most hackneyed example is X-rays. While medical imaging in itself is a great feat, the use of AI has elevated its efficiency. AI-based medical imaging involves the utilisation of algorithms as well as software to ameliorate the reading of medical images.
While some patterns and anomalies may not catch the human eye, this new technology enables such shortcomings to be conquered. This will help the doctors in providing the patient with a diagnosis that is not only almost error-free but also one that helps detect diseases and conditions at a much earlier stage. An improvement as such is a mere base-level capability of AI.
It boasts of other additions such as:
- Advanced Imaging Modalities: Technologies like functional MRI (fMRI), Diffusion Tensor Imaging (DTI), and Positron Emission Tomography (PET scans) have gained fame for their potential to generate accurate and extensive details about tissues and organs. Additionally, there are new and advanced dual-energy CT scans that have replaced the old ones. One of the major drawbacks of CT scans that we are familiar with is the significant radiation exposure that it causes. However, the new variety of CT scans diminishes the radiation doses and provides high-quality images.
- While various developments continue to manifest themselves, one of the latest and most impressive is WBMRI (Whole Body Magnetic Resonance Imaging). This is considered to be one of the most sensitive imaging tests that allow for earlier detection and treatment of multiple myeloma. Not only is this beneficial in terms of long-term health but economically as well.
- Three-dimensional and four-dimensional medical imaging techniques are surfacing because they promise a better visualisation of complex anatomical structures and dynamic processes in real-time. Such models that are either 3-D printed or 4-D printed enable the planning of surgical procedures more efficiently putting the patient at a lesser risk.
- The field of Radiology has paired AI with cloud technologies and created a breakthrough that could potentially change the world. Helping radiologists to battle burnout from the cumbersome volume of image-data sets, Nathan Eddy in his article ‘What’s Next in Medical Imaging with Cloud and AI Technologies?’ illustrates how “AI-based automation can act as ‘virtual residents’, providing accurate interpretations of screening results and aid doctors to plan treatments more effectively”. Not only does AI have the power of flagging anomalies faster than a radiologist but it also has the ability to cross-reference them with past examinations that have similar results, when coupled with cloud technology.
- If you thought that the fact that doctors can look into the human body despite not making a single incision on the body was fascinating, researchers at Monash University are inviting you to think again. They have put forth their new design which is a co-training of a ‘dual-view’ AI algorithm for medical imaging that has mastered the art of mimicking a second opinion.
- Himashi Pieris (A PhD candidate at Monash’s Faculty of Engineering) explains this mind-boggling invention in Science Daily, where she says,
“One part of the AI system tried to mimic how radiologists read medical images by labelling them, while the other part of the system judges the quality of the AI-generated labelled scans by benchmarking them against the limited labelled scans provided by radiologists”. This helps the AI model to arrive at more informed decisions.
Additionally, a recent headline that blew minds worldwide was when academics at the Massachusetts Institute of Technology in the US dropped information on a wearable ultrasound scanner that could detect breast cancer at an earlier stage. This does not mean that patients will not have to go for routine mammograms. Rather, this device, which is a flexible patch that can be attached to a bra, permits the wearer to self-examine and image the breast tissue from different angles by rotating the patch around. Innovations as such, apart from enabling the detection and early diagnosis of breast cancer, not only draw from AI but also contribute to the development of AI algorithms.
It’s no surprise really that Science Daily’s trending topics in the world of medical care during the final week of July show that the most recurring word in all of those headlines was, *drum-roll please* ‘Artificial Intelligence’. AI’s growth spurt in the field of health care has become large beyond comprehension. What was once vicariously experienced through science fiction is fast becoming or has already become a reality and is knocking on the door of the masses. In a corner of a hospital’s bustling corridor or behind closed doors of a cutting-edge laboratory, a technological revolution is taking place, and AI is seated at the head of the table.
(Sandunlekha Ekanayake)