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The market value of AI in the healthcare industry is expected to reach 6 6.6 billion by 2021.
AI technology is also rapidly entering hospitals.AI applications are concentrated in three major investment fields: digitization, engagement, and diagnostics.Looking at some examples of artificial intelligence in health care, it is clear that there are tremendous advances in the inclusion of AI in medical services.Let’s explore some amazing applications of AI that revolutionize health care.Also Read: The Future of Healthcare Sector Will be Around “AI”Robot DoctorsNothing is more exciting than AI robots.
However, these are not human-like droids from sci-fi films.
the same year, the first semi-automated surgical robot was used to stitch narrow blood vessels up to 0.03 mm.Clinical DiagnosisAI algorithms diagnose diseases faster and more accurately than physicians.
They are particularly successful in detecting diseases from image-based test results.Late last year, Google’s DeepMind trained a neural network to accurately diagnose 50 types of eye diseases by analyzing 3D rental scans.
Some types of cancer, such as various types of melanoma, are difficult to detect at an early stage.AI algorithms can scan and analyze biopsy images, and MRI scans 1,000 times faster than doctors.
Machine learning is changing the future of supply chain management.
According to a recent study by Mckinsey Global Institute, advanced AI technologies have the potential to unlock a global economic impact of $10-15T across all industry segments.
Gartner recently projected that by 2020, 95% of supply chain planning vendors will rely on supervised and unsupervised machine learning for their solutions.Increasing costs, Revenue losses, Bad customer service, and reducing profits are all By-product of operational inefficiencies.
For the Supply chain business to survive in today’s competitive and complex market, Machine Learning (ML) and Artificial Intelligence (AI) are considered as the most promising technologies available.The ability for the system to analyze the data, learn, and improve automatically from experience, without any programming is done through Machine learning.
Machine learning is used to identify missing, rogue, or duplicate data points and uses history and historical actions to correct the data.Why and How does Machine Learning is ideally suited to transform supply chain management?
The predictive Analytics technique has the advantage of enabling real-time decisions based on statistical estimates of future outcomes.
