The document discusses the top AI applications in healthcare, including image analysis for disease detection, natural language processing for diagnosis accuracy, and machine learning for oncology and clinical trials. It highlights advancements in robotic surgeries, patient monitoring, hospital management, and patient care through smart devices, showcasing the growing impact of AI on improving healthcare efficiency and outcomes. Swathi Young, the author, is a seasoned technology expert advocating for ethical AI and diversity in the field.

1. Top 10 AI Uses in
Healthcare
Swathi Young
CTO, Integrity Management Services, Inc.
AI/ML Show
https://www.linkedin.com/in/swathiyoung
Twitter / Instagram @swathiyoung
1

2. Healthcare
providers are
looking
at AI-powered
solutions today
to support
Decision-Making,
Improve patient outcomes,
and increase efficiency and
reduce costs

3. 3
IMAGE ANALYSIS –
Diabetic Retinopathy /
Lung cancer

4. Vision loss due to diabetic eye disease is on the rise; image analysis of the retina
using machine learning
can speed up detection of diabetic retinopathy, thereby preventing loss of Vision

5. 5
NATURAL LANGUAGE
PROCESSING (NLP)
Diagnosis reports

6. Electronic Health records follow machine readable formats, however the notes written as
text by physicians/ radiologists can help with accurate and quicker diagnosis.
NLP is used to extract text and unstructured data into
machine-readable format to help research, analyze and
interpret vast quantities of text data

7. 7
MACHINE LEARNING
in Oncology for
Cancer detection

8. Researchers are using deep learning to train machines to
identify cancerous tissues with an accuracy comparable to a
trained physicist. Deep learning holds unique value in detecting
cancer as it can help achieve higher diagnostic accuracy in
comparison to domain experts.

9. 9
AI in Mental Health

10. 10
Many mental health Apps provide emotional
behavioral therapy based on questionnaire
automation and provide mental support, e.g., Tess

11. 11
MACHINE LEARNING in
Pharma for
CLINICAL TRIALS / GENOMIC
RESEARCH

12. Machine learning to re-think clinical trials to reduce the time
to bring a drug to market.
AI/ML is also to using AI and genomic data to gather new
insights about incurable, prevalent diseases.

13. 13
ROBOTIC SURGERIES

14. AI offers numerous opportunities for the advancement of robotic surgery. It
can facilitate interaction mediums between surgeons and surgical robots, for
example by recognizing surgeons' movements (e.g. head, eyes, hand) and
converting them into an action command for the surgical robot.

15. 15
AI for Patient
Monitoring

16. Patient health monitoring has benefited from AI and
has gained momentum since the COVID-19 pandemic.
The data collected through health monitoring devices,
sensors and wearable has led to using AI/ML to deliver
targeted, outcome-based therapies.

17. 17
AI in Hospital
Management

18. Hospital management systems help health care providers and
medical practitioners to help with hospital administration such as
scheduling, admissions, Electronic health records, medical billing,
accounts, claims etc. With the help of AI, these processes are being
automated and made more efficient, and less time-consuming.

19. 19
AI in Patient Care –
interconnected Smart
devices

20. There are many uses of AI for patient care using sensors and smart health devices.
For e.g., Kardia mobile has launched an FDA cleared mobile app along with a finger
pad that that can assess Parkinson’s disease symptoms. The app uses the gyroscope
found in many mobile devices to analyze and quantify tremors, patterns in gait, and
performance in a “finger tapping” test. An AI algorithm differentiates between
actual tremors and “bad data,” such as a dropped phone or the wrong action in
response to the app’s question.

21. 21
PREDICTIVE ANALYTICS
for Fraud Detection in
Medical Claims

22. Machine learning models are used by health care
insurance companies and government to automate claims
assessment and routing based on existing fraud patterns.
This process flags potentially fraudulent claims for further
review, but also has the added benefit of automatically
identifying good transactions and streamlining their
approval and payment.

23. 23
Swathi Young is an international keynote speaker, blogger, community-builder and an award-wining CTO. In her 20+ years of technology
experience, she has led over 100+ projects globally - Belgium, India and the United States across a number of Fortune 100 companies like GE
and Oracle.
Swathi is passionate about using cutting edge, artificial intelligence technologies to increase the performance of organizations. She believes
that the intersection of Artificial Intelligence and humanities is important to focus on as we lay the foundation of AI applications for future
generations.
In 2020, Swathi was selected to be a member of the Forbes Technology Council, where she shares her expert insights in original business
articles on Forbes.com.
Swathi is a brand ambassador for Women in AI, an international non-profit organization whose goal is to increase diversity in AI.
She recently co-authored the Ethical AI framework, a framework to help federal agencies evaluate the ethical outcomes of AI products. She
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