Artificial Intelligence has Opened the Door for Easy Medical Diagnostics

Artificial intelligence in the medical diagnostics market is anticipated to reach US$3,868 million by 2025

Artificial intelligence

Artificial intelligence

Artificial intelligence in the healthcare industry is revolutionizing the way people see both technology, and medicine, and treatments. Starting from allotting time slots for doctor appointments and doing general checkups to providing telemedicine and robot companionship to patients, artificial intelligence is changing the face of healthcare. But one thing stands out of all this. Yes, it is diagnostics. Diagnostics is an important and initial part of healthcare that paves the way for both doctors and patients to get medical support. Fortunately, the recent development in artificial intelligence is improving the medical diagnostic process.

For a long time, artificial intelligence was seen as a technology that could take over human physicians’ jobs. Even though we can’t deny the anticipated apocalypse, for now, it is at a very far distance. However, it took many years for people to realize that AI is something that helps doctors treats their patients in a better way. Especially, physicians are even trusting artificial intelligence in medical diagnostics. The technology helps with medical decision-making, management, automation, admin, and workflow. Artificial intelligence is used to diagnose cancer, triage critical findings in medical imaging, flag acute abnormalities, help radiologists in prioritizing life-threatening cases, find cardiac arrests, predict stroke outcomes, and help with chronic disease management. A recent report ‘Artificial Intelligence in Medical Diagnostics Markey by Components, Applications, End Users- Global Forecast to 2025,’ projects that by 2025, AI in medical diagnostics will reach US$3,868 million from the existing US$505 million with a CAGR of 50.2% during the forecast period. Major tech players are also providing AI healthcare services. Some of them are listed below.

  • IBM’s Watson for Health- The solution empowers clinics, governmental programs, researchers, and patients by offering an apt technological remedy.
  • Siemens Healthineers’ AI-Pathway Companion- It can read the chest CT images, perform automatic measurements, and prepare the medical report with valuable clinical images and quantifications.

Google Health- Google health aids users with their fitness program. It provides information about their medical conditions, nearest hospitals, and reminders to take medicine.


AI in finding the right medicine and treatment

Artificial intelligence can detect both minor and critical diseases. It can even tell whether a patient has a certain condition even before evident symptoms appear. While this could be a simple thing for normal illness, for diseases like cancer, early detection is a life-saving task. Besides carrying out disease diagnostics, artificial intelligence can also provide an outlook on which kind of treatment and medicine would work better on the patient. Modern AI algorithms help doctors arrange a comprehensive approach to disease management.


Image recognition in multiple disease diagnostics

Image recognition in multiple disease diagnostics: Earlier, even though image recognition was used to detect diseases, it was only a handful of diagnosis it could perform. But the technology has evolved so much today that image recognition is being implied to predict multiple diseases. Image recognition is applied to AI algorithms to find the illness. Unfortunately, their value in radiology practices is still limited as the algorithms may overlook or misconstrue signs of disease that they are not trained on, which could lead to misdiagnosis. In the future, image recognition powered by an AI algorithm will be able to recognize conditions that even doctors can’t.


Deep learning helps in the radiology profession

Physicians’ burnout was big trouble that didn’t come to light for a long time. But Covid-19 changed the scenario. A lot of doctors talked about their tight working schedule and the stress that followed over social media platforms. A handful of them even left their jobs, struggling to deliver quality patient care, and juggling complex emotional challenges. In a report, 42% of physicians revealed that they are burned out. Artificial intelligence in medical diagnostics is a powerful tool for reducing physical burnout, but equally for radiology professionals with exceptional support in managing workloads that are only on the spike. Deep learning solutions have been providing radiologists with essential support as they manage their daily schedules. Deep learning helps radiologists in catching urgent cases faster without compromising on their existing workloads or cases.