Artificial intelligence has many applications in healthcare, including improving disease diagnosis through analysis of medical imaging and other patient data, aiding radiologists in detecting abnormalities, and enabling constant remote patient monitoring. The use of AI is expected to lower medical costs through greater accuracy and better predictive analysis. It is being applied to issues like managing the coronavirus outbreak through monitoring patients and regulating hospital visitor flow. Going forward, AI may help predict where virus outbreaks are likely to occur.

1. Role of artificial
intelligence in
healthcare
Submitted By :- GROUP 5
02115101718 - Muskan verma
02215101718 - Nishant khurana
02315101718 - Pooja yadav
02415101718 - Prachi gupta
02515101718 - Prateek chahar
Submitted To: Dr. Deepshikha kalra

2. Artificial intelligence
• Artificial intelligence is the development
of computer system that are capable for
performing tasks that normally require
human intelligence tasks such as
decision making object detection solving
complex problems .
• AI sometimes called Machine
Intelligence

3. Artificial intelligence health care
(AI) in healthcare is the use
of complex algorithms and
software to emulate
human cognition in the
analysis of complicated
medical data. Specifically, AI
is the ability of computer
algorithms to approximate
conclusions without direct
human input.

4. Artificial
Intelligence in
Healthcare
• Artificial intelligence will contribute an
additional 15.7 trillion to the world
economy by 2030 .
• The greatest impact will be in the field
of healthcare ,so we know that
healthcare is getting more importance
or is using artificial intelligence in a
more advanced manner

5. AI different
from
traditional
technologies
AI technology from traditional technologies in
health care is the ability to gain information,
process it and give a well-defined output to the
end-user.
AI does this through machine learning algorithms.
These algorithms can recognize patterns in
behavior and create their own logic. In order to
reduce the margin of error, AI algorithms need to
be tested repeatedly.

6. REASON BEHIND THE SUDDEN
GROWTH OF AI IN HEALTHCARE
INDUSTRY
• High availability of medical data :
AI is based on technologies such as deep
learning and machine learning ,which
require tons of data so with availability of
data it became easier to implement or it
became easier to use artificial intelligence .

7. REASON
BEHIND THE
SUDDEN
GROWTH OF AI
IN HEALTHCARE
INDUSTRY
• Development of complex algorithms :
Machine learning is not capable of
handling high dimensional data as it
contain thousands of attributes . In
order to process and analyze data of
this dimension is hard to do machine
learning but as soon as deep learning
and neural networks was introduced
this became much easier to solve
complex problems that involve high
dimensional data.

8. Growth of AI
AI algorithms behave differently from
humans in two ways:
(1)algorithms are literal: if you set a goal,
the algorithm can't adjust itself and
only understand what it has been told
explicitly,
(2)and algorithms are black boxes ;
algorithms can predict extremely
precise

10. Machine
Learning And
Deep learning
Machine Learning
Machine learning is a subset of Artificial intelligence (AI)
which provides machine the ability to learn automatically &
improve from experience without being explicitly
programmed .
DEEP LEARNING
Deep learning is a collection of statistical machine learning
techniques used to learn feature hierarchies based on the
concept of artificial neural networks .

11. startups
• Large technology companies
such as IBM.and Google, and
startups such as Welltok
and Ayasdi ,have also developed
AI algorithms for healthcare.
• Additionally, hospitals are looking
to AI solutions to support
operational initiatives that
increase cost saving, improve
patient satisfaction, and satisfy
their staffing and workforce
needs

12. Current
research
Various specialties in medicine have shown
an increase in research regarding AI :
Radiology
Imaging
Disease diagnosis
Telehealth etc…

13. Radiology
• The ability to interpret imaging results with
radiology may aid clinicians in detecting a minute
change in an image that a clinician might
accidentally miss. A study at Stanford created an
algorithm that could detect pneumonia at that
specific site with a better average F1 metric (a
statistical metric based on accuracy and recall), than
the radiologists involved in that trial.

14. imaging
• imaging, it is the use of
various techniques to generate
images of the structure and/or
function of the brain or any other
part of the nervous system.
• Recent advances have suggested the use of AI to
describe and evaluate the outcome of maxilla -facial
surgery or the assessment of cleft palate therapy in
regard to facial attractiveness or age appearance.

15. Disease diagnosis
• There are many diseases and there also many ways that AI
has been used to efficiently and accurately diagnose them.
Some of the diseases that are the most notorious such as
Diabetes, and Cardiovascular Disease (CVD) which are both
in the top ten for causes of death worldwide have been the
basis behind a lot of the research/testing to help get an
accurate diagnosis.
• Medical imaging and diagnosis powered by AI should
witness more than 40% growth to surpass 2.5 billion U.S
dollars by 2024 , that was found in global market insights .

16. Telehealth
• A wearable device may
allow for constant
monitoring of a patient and
also allow for the ability to
notice changes that may be
less distinguishable by
humans.

17. implication
• The use of AI is predicted to decrease medical costs as there will be more
accuracy in diagnosis and better predictions in the treatment plan as well
as more prevention of disease.
• Other future uses for AI include Brain-computer Interfaces (BCI) which
are predicted to help those with trouble moving, speaking or with a
spinal cord injury. The BCIs will use AI to help these patients move and
communicate by decoding neural activates.

18. Hospitals Tap AI to Help Manage
Coronavirus Outbreak
• Large health-care systems are turning to
artificial intelligence to monitor patients
and to regulate the flow of visitors as they
attempt to contain the spread of the novel
coronavirus.

19. AI for Virus Detection and
Prevention
• Other companies, such as Metabiota, are also using
data-driven approaches to track the spread of the
likes of the coronavirus.
• If the work of scientists Barbara Han and David
Redding comes to fruition, AI and machine learning
may even help us predict where virus outbreaks are
likely to strike

21. Thank you