The scope of application of AI-driven technologies in Healthcare is increasing. It seems we are approaching a world where our connected devices tell us when we need to visit our doctor because they have detected symptoms that might be concerning. An explosion of data and computer vision technology has extended a helping hand to medical professionals in decision-making.
As per a report by Verified Market Research, computer vision in Healthcare Market was valued at USD 229.58 Million in 2018 and is projected to reach USD 5317.75 million by 2026, growing at a CAGR of 48.13% from 2019 to 2026.
Computer vision has been around for several decades, but it has recently become a hot topic in the healthcare industry. With the help of computer vision technology, medical practitioners are now able to deliver greater accuracy when it comes to diagnostic procedures, and they can even take care of patients remotely through Conversational AI bots and virtual assistants. This aids the healthcare workers and medical professionals to focus on important tasks that need human intervention as certain processes can be automated through these virtual assistants.
Computer vision has drastically changed how doctors practice their art. From new technology that provides quicker diagnoses to wearables that continuously monitor vital signs and send out alerts if something is off—computer vision helps healthcare organizations provide better care delivery. Here is how computer vision can help augment healthcare services.
Early detection of cancer is significantly important for improving cure rates and survival rates. Traditional methods of diagnosing are largely inaccurate, however, there has been a recent upsurge in using computer vision to diagnose cancers such as skin, breast, ovarian, and prostate cancers. Computer Vision helps in carrying out in-depth analysis and early detection of grave diseases like cancer.
PathomIQ Inc. an AI-enabled computational analysis platform, wanted to enhance its Image processing techniques to allow earlier detection of abnormalities and treatment monitoring. Mantra Labs built and trained AI models on relevant medical data to find specific malignancy patterns that helped them in the detection of high-grade cancer cells.
Today, surgeons can easily rely on medical imagery derived through cutting-edge technologies such as machine learning and computer vision for assistance during an operation. A simple task such as examining an x-ray of a broken bone when analyzed using computer vision can help improve surgical success rates by eliminating possible human errors. Further studies focus on applications of computer vision in monitoring chronic diseases, heart surgeries, and preventative care.
Computer vision is helping dermatologists in detecting skin cancers with high accuracy. AI algorithms can detect small abnormalities in images of skin lesions and determine which ones need biopsies. This helps avoid invasive procedures on healthy people and confirm diagnoses in those who need it.
According to a paper published in ScienceDirect by Umm AL-Qura University’s Department of Computer Science and Engineering, a method is offered for the dissection of skin illnesses utilizing color photographs without the requirement for medical intervention. The method had two steps, and the accuracy was remarkable at 95.99 percent for the first stage and 94.016 percent for the second stage when tested on six different forms of skin conditions.
There are a growing number of companies combining computer vision with AI technologies such as machine learning, natural language processing (NLP), and deep learning to develop innovative products that will transform medicine. For example, using self-driving vehicles for patient transportation. Combining computer vision with AI also means medical applications don’t need to be at medical facilities—they could be integrated into existing or future systems. Imagine simply plugging your smartphone into an algorithm designed to detect cardiovascular disease and having immediate results in real-time!
Though it comes with certain challenges such as lack of technical knowledge, hesitation to adopt AI-based technologies, the possibility of technical errors, dearth of skilled professionals, etc. However, with rapid digitization in the world, the application of these new-age technologies will grow exponentially.
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