MarketsandMarkets reveals the computer vision market is expected to grow from USD 10.9 billion in 2019 to USD 17.4 billion by 2024, bringing disruptive leaps in a host of industries and business domains. Broadcasters, manufacturers, and banks are leveraging this innovative tech to increase operational efficiency and revamp customer experience.

Healthcare doesn’t stand still, either. And in this feature, we’ll show how computer vision is writing the next chapter for medicine.

Ensuring Rock-Solid Security

Apart from securing vital PHI and other data from cyber-attacks through HIPAA compliance, hospitals also need an extra layer of physical security. This can be achieved with surveillance cameras and advanced face recognition software.

Security personnel can scan anyone entering the hospital and perform a thorough analysis of an individual’s face and its attributes such as hats, glasses, age, gender, head pose, eye and skin color, eyebrow types, nose tip, and more. This information can be effectively used for establishing advanced hospital access control.

The system will be able to recognize individuals who had previously been denied access to the facility as well as identify potential drug seekers.

Improving Patient Satisfaction

Just as retailers and other product and service providers analyze customer emotions to gauge satisfaction, healthcare institutions can perform comprehensive visual emotion recognition to boost patient experience.

To identify patient reactions — including happiness, anger, sadness, surprise, disgust, and fear — over the full care cycle, you need to apply sophisticated video analytics. The obtained results are then translated into interactive dashboards featuring satisfaction scores.

Upping the ante in emotion recognition, perform an extensive voice analysis, assessing your patients’ voice power, pitch, speed, and formant frequency. This data will help you better understand patient reactions for improved satisfaction and engagement.

Medical Image Analysis: Identifying Problems Faster

Computer vision also represents a well-oiled machine set to enhance diagnostics and treatment — by thoroughly analyzing CT, MRI, PET, ultrasound, radiography, mammography, and other types of medical images.

One of the implementation in this regard is a pathology slide review. Given the complexity of this task, there can be substantial variability in the diagnoses given by different clinicians for the same patient. Trained on massive data amounts, a computer vision-powered system will be able to deliver more accurate results when detecting abnormalities in heart, brain, lungs, liver, and other organs.

The examples of such machine-aided diagnostic screening vary from detecting breast cancer in lymph node biopsies to reading retinal fundus images for diabetic retinopathy to analyzing three-dimensional images for accelerated genomics problems discovery.

Enhancing Equipment And Product Quality Control

Quality control is another area where computer vision makes strides. Coupled with IoT, this tech is able to enhance the drug manufacturing process and medical equipment monitoring.

By leveraging video analytics and data obtained from sensors, you can easily detect surface imperfections, foreign objects, and other irregularities that negatively influence product quality — during both the production line and packaging stage.

Quality control cameras can also be used in health facilities for sending alerts when medical equipment like MRI machines or dental hardware goes sideways.

Revamping Treatment Monitoring

Machine vision is not a behind-the-scenes player in monitoring a patient’s adherence to the prescribed medication.

For example, a mobile app equipped with advanced object and face recognition can help clinicians examine whether their patients ingest the necessary pills and send reminders to those who dropped out of the therapy, reducing attrition.

Coupled with ML, computer vision vastly improves patient rehabilitation. A case in point: based on a video analysis of changes in motor skills, the system recommends optogenetic stimulation adjustments, aiding in stroke patient recovery.

Where Do We Go from There?

From improving physical security and patient engagement to enhancing diagnostics and treatment monitoring, computer vision steps in to revamp care. Hospitals around the world have already started reaping the benefits. Are you ready to follow suit?

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