https://www.datatobiz.com/blog/computer-vision-in-health-care/

1. COMPUTER
VISION IN
HEALTHCARE
Need of the Hour?

2. How AI could benefit Health Care
Industry

3. AI could engage in repetitive tasks, like examining vast amount of X-Rays, Data
Entered and various scans.
AI can be fed massive amount of past patients data and could help us arrive at
a conclusion.
Can help us minimize the minor errors in learning diagnostics.
Develop to-the-point drugs, maintain medical records, etc.
Digital Nurses and Health Bots are future. They’ll provide required consultation.
There have been discussions on how AI could help various industries and Health
Care is one of the most talked. There are many ways AI could support the industry.
AI is a vast field and can be confusing on what specific model to use. There have
been continuous discussions and multiple methods approached and improvised.

4. For the purpose of classification and regression, Support Vector Machines can
be implemented. Here support vectors are data points, which are closest to the
hyperplane. To diagnose the Cancer and other neurological diseases, SVMs are
widely used.
Support Vector Machines
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5. We now have large amount of data which is composed of examination results,
texts, reports, notes and importantly, discharge information. Now, this data
could mean nothing for a machine which has no particular training for reading
and learning from such data. This is where NLP could be of use, by learning
about keywords related disease and establish a connection with historical data.
NLP might have many more applications based on needs.
Natural Language Processing

6. Implementing hidden layers to identify and establish a connection between
input variables and the outcome. The aim is to decrease the average error by
estimating the weight between input and output. Image Analysis, Drug
Developments and few, are the fields where Neural Networks are harnessed.
Neural Networks

7. Convolution Neural Networks, over the time has rapidly being developed and currently is
one of the most successful computer vision method. “CNNs simply learns the patterns
from the training data set and tries to see such patterns from new images.”. This is same
as humans learning something new and implying the knowledge but what all these
models know is series of ones and zeros.
With accuracy of 95%, a CNN trained at University of South Florida, can quietly easily
detect small lung tumors, often missed by human eye. Another research paper suggests
that cerebral aneurysms ca be detected using deep learning algorithms. At Osaka City
University Hospital, they detected cerebral aneurysms with 91-93% of sensitivity.
RNNs, which are Recurrent Neural Networks are also popular and could be of great used
as they are the neural networks but with information in sequence. Performing a same
task for multiple elements and composing output based on last computation.
As Always, CNNs are the Best

8. Acquired by Google in 2014, Deep Mind has outplayed many players and has set
new record in AI for Health care Industry. Protein Folding is something they have
been working on and reached a point where predicting the structure of protein,
wholesomely based on its genetic makeup, is possible. What they did was relied
on Deep Neural Networks, which are specifically trained to predict protein
properties based on genetic sequence. Finally they reached a point where they
had the model predict the gap between amino acids and the angles connecting
the chemical bonds which connects earlier mentioned amino acids.
This could also help in understanding the underlying reasons of how genetic
mutation results in disease. For whenever, the problem with Protein Folding will be
solved, it will allows us fasten our process like drug discovery, research, and
production of such proteins.
How Google’s DeepMind sets new milestones

9. It is not a new discovery that machine learning can fasten the Drug
Development Process for any disease or virus. There are very few datasets
available related to Corona and has a lot to tackle in order to establish a
conclusion.
Recently, there have been developments involving AlphaFold, which is a
computational chemistry related deep learning library.
How could this help in aiding Corona
(COVID-19)
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https://www.datatobiz.com/blog/computer-vision-in-health-
care/