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How AI-Based Medical Image Analysis Will Benefit Medical Industry

Not very long ago the medical industry was taken by storm with the idea of Artificial Intelligence being used in medical imaging and its analysis. With time now the question of ‘will it replace me?’ has changed to ‘how will it help me?’ in the medical industry with the arrival of the artificial intelligence solutions.

So while Artificial Intelligence programming is used in various fields of medical industry like Image analysis, cognitive workflow applications, usage of intelligent medical imaging machines, etc, this article will specifically showcase how AI based medical image analysis will be beneficial for the medical industry.

AI-Based Medical Image Analysis is on the rise

A recent study conducted by Frost & Sullivan noted that the majority of the 114 startups that are active in AI medical imaging are targeting the market with AI-based medical image analysis. With images being the largest data source in the healthcare system and most difficult to analyse, the clinicians have very little choice but to depend on the overworked radiologist to analyse the images. The vital aspect of a radiologists’ job is identifying and analysing particular features in the image. Based on the findings of analysing these images is the vital clinical step in the imaging workflow.

As a result of this startup disruption with various healthcare app development, the primary focus is on the image analysis with AI. Hence to be part of the changing market the AI-Rad Companion Chest CT has been debuted by Siemens Healthiness. The software used in the machine can show the CT images by highlighting various thoracic structures and mark any potential abnormalities.  GE Healthcare has also brought in the market the Edison, which collects all the existing AL algorithms into a single platform.  

Who Benefits from the Artificial Intelligence Programming of Automated Image Analysis?

The automated image analysis based on artificial intelligence solutions can be beneficial for the entire healthcare system.  But there are three key stakeholders of the medical industry who are said to be on the first line of receiving the benefits from AI- based medical image analysis.  

Radiologists: There is an ever-growing volume of images and data captured by X-rays, CT, MRI, PET, and Ultrasound but there are not enough radiologist. Hence there is a significant gap between the demand and supply between the number of radiologists and the inflow of data. As a result of this, the radiologists are overworked and the National Health Service of UK has warned that the radiologist service may collapse entirely if the shortage continues.

The automated image analysis offered by the Artificial Intelligence programming will alleviate the burden on the radiologists by reducing the need of them having to go through and scrutinize every image to identify any anomalies. Instead, the clinicians can focus on the images that already flag those anomalies with deep learning algorithms.  Even to the radiologists, the AI can suggest the nature of the detected abnormalities. 

Non-Radiologist Clinicians: As part of the Artificial Intelligence solutions, the AI imaging analysis will allow the radiologist to focus on diagnosis and decision-making process by freeing him/her from scrutinizing the image. The AI-based image analysis will also allow the non-radiologist clinician to understand and interpret the images without becoming dependent on the radiology departments.

Generally, a good clinician is able to do a straightforward diagnosis of the images mainly if they are ultrasounds. With the analysis provided by the AI, the capability of the clinician will be extended.

Patients: The AI image analysis will be immensely beneficial for those that the technology intends to serve, the patients. They will be able to get their reports and analysis in a timely fashion without having to wait for weeks to get and understand their x-ray reports.

The self-monitoring healthcare applications will increase including self-scanning solutions that are wearable with the help of healthcare application development using AI. The patients will be less exposed to invasive and painful procedures. Patients will have less interaction with drugs that leave toxic and radioactive traces in their bodies. Additionally, less CT scans and X-rays will be needed with the AI based image analysis

It has already been established that image analysis by the AI in the medical industry will be beneficial to these three primary stakeholders. But the question remains how will it be delivered?  

How will these benefits be delivered by AI-based image analysis?

The best way to demonstrate how innovation will be delivered is by a couple of examples:

The CT scan becomes 3D:  That is instead of the 2D slices the patient’s images are provided in 3D and with the innovation of deep learning solutions the analysis can be done. There has bee the launch of deep learning technology by Aidoc that does the full-body solution CT scan analysis. It will allow the radiologist a workflow –integrated application, enabling them to analyse each part of the scan without requiring them to switch between separate analysis of the images. 

MRI Gets Boost in Speed Power and Comfort: Many prefer to do MRI because it does not involve the radiation that CT scan has, however, the time taken for getting an MRI result is more than CT scan. The Arterys a company in San Francisco have used AI imaging analysis and has been able to not only cut down on the time taken to get the MRI done but also improved the quality and quantity of the data given for cardiac MRI. Also, at times a patient had to hold their breathing, but with this technology that is no longer required during the MRI.

These two examples of how the benefits can be delivered. The AI-based imaging analysis will be helpful in PET scans, as well as Ultrasound.

To know the benefits of how AI imaging analysis and the AI itself will help the people a study was recently conducted. It had several categories to determine the benefits of healthcare app development with AI. The scale was between 0 and 5, with 0 being the point of lowest satisfaction while 5 being the highest. Here are the categories and how they were rates.

  • Improve health outcomes: 4.25
  • Improve healthcare quality: 4.2
  • Saving money: 4.1
  • Saving time: 3.9
  • Customers want to be seen as an innovative leader or supporter: 3.8
  • Improving revenue: 3.75
  • Improving healthcare related workflows: 3.6
  • Improving diagnostic accuracy: 3.5
  • Improving speed to market: 2.9 

So while AI had taken the medical industry by storm a few years ago, it is now proving to be quite beneficial for in the healthcare system with its healthcare apps and other AI-based developments. 

Written By

As the Founder and COO at Cyber Infrastructure Inc, it is my aspiration to drive our global clients ahead in the competitive technology world by enabling them to receive huge financial and operational benefits in software development through my years of experience and extensive expertise as technology adviser and strategist.

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