$11.32 billion was the market size of the global Computer Vision industry in 2021. Its CAGR is expected to be 7.3% from 2021 to 2028. Computer Vision has amazing benefits in healthcare app development solutions, making it a prime technology for pattern recognition, diagnosis, imaging, and more.

The market for Computer Vision in healthcare is expected to grow at a CAGR of 47.2% and will reach $1.46 billion by 2023. It is already assisting doctors to better diagnose their patients, find diseases much faster than before, and deliver treatments early on in the illness.

But what exactly is Computer Vision? Let us find out.

What is Computer Vision?

Computer Vision is a form of Deep Learning technology that utilizes algorithms to imitate human Vision. However, it is much faster and more accurate than human vision. Through regular training, algorithms scan through images and find patterns. They classify, cluster, categorize, and collate similar objects to make sense of the pattern.

Today, Computer Vision is nearing 99% accuracy when it comes to pattern recognition. This is highly useful in healthcare. While health care application development services proliferate, they need advanced technology that can improve patient outcomes.

Analysis of medical patterns and images help doctors recognize diseases early on. Computer Vision and Deep Learning now combine to offer in-depth analysis of a patient’s physical ailments. 

advantages of using computer vision in the healthcare industry

(Source: Vilmate)

One of the biggest advantages of Computer Vision is that it can identify signs of illnesses that might develop later in life. Healthcare web application development consistently incorporates Computer Vision to scan a person’s vitals and find the right treatment at the right time.

Read More: Top 10 Most Popular Healthcare Applications Examples

Let us see now how Computer Vision assists doctors and clinicians in healthcare.

5 Top ways Computer Vision is Transforming Healthcare

Computer Vision works with tremendous amounts of data. Healthcare apps and solutions gather enough data so that Computer Vision can make accurate reports. From diagnosing cancer to identifying hereditary diseases, it has transformed the imaging and recognition of illnesses.

Here are 5 ways through which Computer Vision is finding its usefulness in healthcare:

  1. Better Image Analysis:
    • Medical imaging is crucial when it comes to disease diagnosis. However, doctors go through hundreds of images every day. It becomes tiresome and troubling.
    • Computer Vision, along with other mhealth app development solutions, offers better image analysis. It can identify patterns and details that might go unnoticed by the doctors. The technology has improved to a great extent that it can identify almost 99% of problems from the image.
    • Computer Vision speeds up the process of analyzing images. In the meantime, doctors can focus on finding the best treatment plans for patients. The technology analyzes images and catches details that might hint towards upcoming diseases as well.
  2. Accurate Blood Loss Gauging:
    • One of the most common causes of mortality in childbirth is postpartum hemorrhaging. By looking at the images of surgical sponges and suction canisters, AI-based Computer Vision can detect the amount of blood loss during the process.
    • Orlando Health Winnie Palmer Hospital for Women and Babies uses such technology to identify the amount of blood loss during childbirth. Before the implementation of Computer Vision, it was difficult to estimate how much blood the mother lost.
    • As the hospital started using Computer Vision, it showed that the doctors tended to overestimate how much blood loss took place during childbirth. Now it has become easier for them to assess and more accurately, leading to treating women in a much better manner.
  3. Minimizing False Positives:
    • Today, professional healthcare app development focuses on providing accurate health care diagnoses. However, false positives are more common than people think. This leads to expensive procedures and treatments that often lead people to put a hole in their budget.
    • A medical app development company that integrates Computer Vision creates features to minimize false positives. The inherent quality of Computer Vision is to be high in accuracy. Therefore, doctors get an accurate diagnosis of a person and identify whether they have a particular disease or not.
    • On the other hand, it also minimizes false negatives. Doctors might miss a couple of details in the medical imaging process. Computer Vision goes through the slightest detail and recognizes every single aspect of the diagnosis.
  4. Diagnosis Cardiac Diseases:
    • Across the globe, cardiac diseases are one of the leading causes of human death. Many times, they are not detected on time, or doctors do not have the required information to make treatment decisions.
    • Computer Vision helps to automate cardiac pathology and offers vascular imaging. It detects anomalies in the heart and provides a report of what is going on. The technology also visualizes the arteries and blood flow in the system.
    • Doctors often need to understand the variables in cardiac MRI, and Computer Vision can help with that. It also offers electronic segmentation, offering a better view of the cardiac disease that may have grappled the patient.
  5. Cancer Detection:
    • And finally, one of the most important and widely known use cases of Computer Vision in healthcare is cancer detection. Today, Deep Learning and Computer Vision have reached physician-level accuracy in diagnosing cancer.
    • Any software development company that builds Deep Learning solutions knows its importance in cancer detection. Skin Cancer, for example, may not be differentiable from other skin ailments. However, with enough data and images, Computer Vision can recognize the healthy tissues from the cancerous ones early on.
    • From lung cancer to blood cancer, Computer Vision has shown tremendous results in the detection of this lethal disease. It can identify the healthy cells from the unhealthy ones and prepare a report and minimize the chances of human error in cancer detection.

Read More: Top 10 Mobile Healthcare App Development Trends 2022

Conclusion

While image and pattern recognition are two of the most excellent use cases of Computer Vision, it is going beyond that. Patient monitoring, remote health monitoring, medical training, and more such use cases develop as the technology progresses. Today, doctors worldwide use Computer Vision to quickly diagnose patients and create a treatment plan early on in the process, leading to better healthcare outcomes and a higher rate of saving lives.

Whether you are looking for an enterprise software development company or the best healthcare app development company, BoTree Technologies is both. We are experts in creating healthcare solutions with Computer Vision, Deep Learning, NLP, and AI to ensure patients and doctors get the best healthcare outcomes.
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