(Newswire.net — September 24, 2020) — Computer vision is a technology on the rise. Once an almost futuristic technology, it has powered a lot of useful products and services that are a part of our everyday lives. The global computer vision market is expected to grow at a 7.7% CAGR, reaching USD 18,24 billion in 2025, according to Grand View Research.
But while self-driving cars and effortless KYC verifications are nice-to-have, there is a much bigger industry out there where computer vision can literally save our lives – healthcare.
For an industry that is heavily image-based (think, CT scans, and MRIs), computer vision is a great fit. It can significantly improve medical imaging analysis, predictive analysis, or healthcare monitoring. Additionally, the technology can assist a more accurate measurement of things like blood loss count during surgeries,body fat percentage, and spectroscopy with advanced oem spectrometers.
Quicker diagnoses and treatments
False positives and false negatives are an ongoing problem in the medical community. Patients are, from time to time, diagnosed with a disease they don’t have and put through unnecessary treatment. Or their ailments are not discovered in time, and they can’t be treated. For breast cancer alone, false negatives can be between 8-10%, according to the Breast Cancer Detection Demonstration Project (BCDDP)
Wrongful diagnoses, no matter what way they swing, have a big financial and mental toll on the society, and computer vision has the potential to eradicate a lot of that toll.
Computer vision solves a significant problem: doctors not recognizing signs of a condition in images, either because they don’t know what to look for, or because the signs are too small to be detected by the human eye.
The latter is, perhaps, one of the most impressive capabilities of computer vision. With their level of precision that far surpasses human eyes, computer vision can detect conditions at much easier stages.
This is especially important for diseases that can be treated efficiently if diagnosed early but may have fatal outcomes if detected later on, such as cancer. The same can be said about rare conditions.
Mount Sinai is one of the many hospitals that uses computer vision to provide faster diagnoses by using AI to analyze CT scans. The AI can provide a diagnosis within 1.2 seconds, which is 150 times that they could do before. Compared to the days or weeks it can normally take, the time savings can mean a faster start of treatment and saving more lives.
Freed time can be spent somewhere else
In many countries, one of the biggest complaints patients have with their GP is short visits. It’s not a secret that many healthcare facilities are understaffed and operate under strict governmental efficiency regulations. Put together, this results in less time dedicated to each patient.
Some of the negligence can, of course, be explained by the level of care the GPs put into their work. But more often than not, doctors are simply too overwhelmed with other tasks to dedicate more time per patient.
With computer vision taking over more of the diagnosing, the time to analyze reports and images can be lessened significantly. It will free up time that can be spent with the patients and provide more personalized care.
The use of computer vision in healthcare can also support doctors to deliver preventive care, and thereby decrease the chances of conditions developing in the future.
Improve the results of clinical trials
It’s quite clear that computer vision applications have the ability to improve the state of the healthcare system as it’s today. But it can also shape how our healthcare systems will function in the future.
A few companies are leveraging computer vision and advanced data analytics to improve the results of clinical trials. Such solutions have non-invasive methods of collecting and analyzing visual and auditory data through the trial participants’ phone cameras and microphones.
These collection methods remove a lot of bias and misunderstanding that can arise when trial participants report their physical and psychological symptoms themselves. This results in greater accuracy that is needed to elevate the integrity of clinical trials.
Scientists can improve their understanding of disease symptomatology, drug dosing side effects, and stratified disease variations, ultimately supporting improved health and trial outcomes
Take care of your skin without leaving the house
Dermatology is another part of the healthcare industry that has embraced computer vision. This is no surprise as it has a lot of overlap with the beauty industry, which has had great success in enhancing the shopping experience for their consumers.
A startup in the UK har combined data science with dermatology to provide personalized skincare plans, all with the help of a smartphone. The company uses photos of the patients’ skin to determine their skin type and any skincare conditions.
While they do also supplement with video calls with licensed dermatologists, a lot of skincare plans they provide are based on photos and a questionnaire alone.