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Improving Diagnosis with Computer Vision Applications in Healthcare
 
 

Artificial Intelligence (AI) is showcasing transformative potential to streamline and improve therapeutic and healthcare practices. From predictive analytics to computer vision, AI technologies are breaking through traditional medical techniques to accelerate and scale multiple treatments. In an attempt to contribute to the current pandemic, Oodles AI is exploring how computer vision services can advance healthcare facilities effectively. Here are some data-driven computer vision applications in healthcare that deploys machine learning algorithms for diverse medical purposes.

Medical Image Recognition

From X-rays to CT scans and MRIs, medical professionals are required to examine complex images to analyze patient health and initiate diagnosis. Diagnostic imaging techniques are critical for qualitative as well as quantitative visual assessment to deliver various healthcare services. However, manual efforts are inefficient at identifying microscopic anomalies in medical images accurately.

The advent of AI has revolutionized image processing technologies such as computer vision. Leading providers of artificial intelligence services are innovating traditional practices with computer vision for optimizing and scaling treatment across specialties. Computer vision is beginning to replace traditional image processing techniques with neural networks to automate the following medical processes-

 

 
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