The future that sci-fi films promised us has come to reality: advanced technology has found its way into many areas, including the medical sphere. Nowadays healthcare is deeply connected to AI and computer vision as many operations demand the usage of modern tech tools. What is more, AI facilitates groundbreaking medical solutions, making them more accurate, efficient and accessible. In this article, we will explore the 10 most recent computer vision use cases in healthcare and how they affect our life.

Vitals checking

Nowadays, it’s not uncommon to have a wearable device that provides us with all the information about our body: our physical and sleeping activity, heart rate, breathing tempo, oxygen and sugar levels in the blood, and even stress markers.

Thanks to the advancements in technology, it has gone further than that: now there is a contactless AI method to measure all human vital signs using standard smartphone cameras. With the help of deep neural networks, computer vision can accurately detect face characteristics and monitor them with optical flow methods. Afterward, AI ‘deciphers’ the acquired data, giving real-time vital sign evaluation that allows clinical specialists to receive and utilize the information for diagnosis purposes.

Smart decisions

Speaking about diagnosis, AI and computer vision are now the last word in this field. These days, they provide an accuracy level that often surpasses human capacity, enabling faster and more precise diagnosis. AI algorithms have got so med-savvy, they can now be used as an interpreting tool for medical images such as X-rays and MRIs.

Thanks to their ability to scan through and promptly detect anomalies, they can spot tumors, fractures, and other things that may easily escape the attention of the human eye. However, the technology is not perfect yet: there might be ambiguity of interpretability that can create misunderstanding among healthcare workers.

Early disease detection

Sometimes, detection at an early stage can save a life, especially when it comes to cancer or brain tumors. In these cases, the future of a patient might be significantly impacted by the timing of diagnosis. Computer vision applications do not only detect diseases early but also create the most efficient strategy and minimize human errors, improving patient prognosis.

Now, AI is capable of successfully detecting the imperceptible signs of different kinds of cancer. In the future, CV disease spotting technology will be more widespread as it develops and gets more integrated into many medical procedures.

Surgery assistant

AI has brought several benefits to the operating table, from being a doctor’s ‘third hand’ to providing a more accessible medical service. By studying myriads of surgical methods, AI can suggest the most successful strategies, even if those weren’t previously considered by human surgeons.

In addition to that, AI solves the problem of surgeons’ cognitive and physical overload. It can accurately determine the best tools and techniques to perform complex tasks in real-time. There is also a robotic surgeon with built-in computer vision technology: it works with accuracy that is beyond human ability and is able to perform many operations in a row without any physical fatigue. Computer vision in healthcare is a crucial invention that enables medics to work anywhere in the globe and help those who lack access to surgical care.

Aftercare tool

AI technology may also be helpful throughout the recuperation period: for example, to track patients’ rehabilitation therapies. Computer vision in healthcare can check if a doctor has prescribed a series of exercises to regain mobility and whether they are being done on a regular basis. Electronic health record systems are growing in popularity because they gather individual health data and leverage AI to process it. When AI recognizes patterns that might present health risks, it can notify medical professionals or caregivers right away, enabling prompt and possibly life-saving intervention.

New wave of education

Computer vision systems have gained popularity in many applications, including healthcare professional training. Healthcare workers now have more alternatives than just traditional educational approaches.

Now, AI has the potential to assist a wider range of medical specialists by ensuring that more doctors have access to tutoring opportunities from the top models in their area. Similarly to pilot training, medics who study surgical and therapeutic methods can gain extensive experience and obtain high-quality evaluations with the help of AI. The simulations’ greatest advantage is that it enables “learning from mistakes.” Such a practical approach that allows students to grow from their mistakes plays an enormously essential role in productive learning and could boost the efficiency and speed of studying, providing the world with highly qualified specialists.

Medical imaging

A specific method that generates a three-dimensional depiction of the internal body is called medical image analysis. In order to make an accurate diagnosis, medical professionals can look at 3D organ scans of their patients using computer vision. Additionally, it improves the resolution of the image by spotlighting difficult-to-see details. Deep learning has also greatly increased the sensitivity of anomaly identification, which has decreased the number of invasive procedures performed and provided insightful information about the human body.

Online healthcheck

Why not use computer vision to track the onset of minor illnesses instead of annual visits to the doctor? Some businesses have already begun implementing this technology. Modern computer vision models can identify any physical flaw, from tooth decay to skin imperfections, with outstanding correctness. Some AI algorithms have become even more competent than medical professionals in spotting skin cancer. Currently, all it takes is a tap on your smartphone to identify potential risks by frequently taking pictures of your body’s moles. Computer vision in healthcare is already able to detect any alterations in the moles’ size, form, or pigment.

Clinical trials improvement

The phase of clinical testing is crucial. Tests may only be considered successful if they are conducted in a proper and supervised way. The issue is that a large number of applicants are turned down before the clinical study even begins, making it an expensive and time-consuming procedure. For this reason, pharmaceutical companies are always coming up with new methods to make it better – AI saves the day once more. Now research can be done more quickly and efficiently as AI will help to pick a perfect match for the trial, taking into account the human factor and other affecting conditions.

Procedure automation

Automation has revolutionized modern medicine, providing accuracy and speed in minimally invasive surgeries, cell tracking, and counting, diagnostic testing, patient data collection, disease tendency definition, etc. Clinical trial time and effort can be decreased by using computer vision to uncover important information in a variety of medical domains. It holds much potential to dramatically minimize mistakes caused by manual labor and save a substantial amount of money, time, and human resources that are scarce nowadays.

Final thoughts

As we see, AI technology has pushed medical solutions far forward, changing the usual clinical approach in many ways. Needless to say, computer vision will be actively incorporated into more procedures, promising to become a leading tool in the sphere and launching the healthcare industry to new heights. As the technology is still evolving, more and more industries come to leverage the potential of AI and CV in their projects. Explore other computer vision projects from OpenCV.ai and find out how you can make it work in your case.