2020. It sounds like the name of a futuristic science-fiction movie or TV show, doesn’t it? Maybe it is. And like our favorite sci-fi flicks there are cutting edge changes happening in real time. We’re the characters in this story and the Computer Vision and Artificial Intelligence partnerships in healthcare are moving fast to help us take care of ourselves.
When computers can see what we can’t. When AI can help us make more informed decisions. When the two are combined to help doctors and providers work more efficiently to save lives, that’s when the cutting-edge shines. From the collaboration of Johns Hopkins, the CDC, and the WHO mapping out the data to contact traces to medical professionals on the front lines, we’ve been focused on one thing. Saving lives.
But, what about the other medical issues that affect us? Heart disease. Cancer. Neurological illnesses.
What if the latest advances in healthcare could help here
Five Ways Computer Vision Helps Healthcare Providers
- Identifies leading causes of medical illnesses in a time-sensitive manner by creating algorithms for image processing, classification, segmentation, and object detection.
- Develops deep learning models to create neural networks.
- Collaboration of teams of scientists working together for the advancement of projects and present findings to business leaders, stakeholders, and clients.
- Allows providers to spend more time with their patients.
- Optimization of medical diagnoses using deep learning so doctors can spend more time with patients to help see and solve the problem faster.
Computer Vision Engineer Meets AI Professional
Artificial Intelligence (AI) offers real world answers in healthcare the world needs today. Computer Vision Engineers build the means to which AI helps providers, patients, and leaders make informed decisions.
Core requirements for both roles include, but aren’t limited to:
- Experience in machine learning and deep learning.
- How to build computer vision algorithms and probability models.
- Problem-solving skills, creativity, ingenuity, and innovation.
- Languages like Python, R, Hadoop, Java, and Spark.
- Be able to see the big picture while at the same time finding the devil in the details. Always striving to improve, to make better, to advance the technology within the industry.
The Challenges and the Potential of Technology in Healthcare
At the moment, Computer Vision, AI, and other healthcare technology models are localized to individual placements. The next step is to have these technologies ‘speak’ to each other across hospitals, provider’s offices, telehealth applications, and electronic health records management for a more cohesive benefit of care.
As this year rounds to a close, we know the vulnerabilities of our healthcare system, and can find solace in the though that technology is bringing it forward at lightning speed. Automation and telehealth appointments have made it a breeze to talk to our doctors and get results faster. We can pay our bills with the click of a button and even carve out a payment plan, if need be. All without leaving our homes.
The data now available to us and our providers offers a foundation, a benchmark of information, so our doctors can make more informed decisions. This data goes beyond the individual, it helps set a precedent for not only individuals, but also entire populations, to help us identify future health issues, epidemics, and pandemics.
Stored data is private and stays within its construct of hospital or doctor’s office, but from it we can create models to plan for the future.
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