artificial intelligence in healthcare made by me and team members. Hope you will find it helpful. Your feedback is essential . Thank you:)

1. ARTIFICIAL
INTELLIGENCE
IN
HEALTHCARE
BY: SHREYA MISTRY
ARPAN GHOSH
SWARNANIL
SARKAR
INGIT PAUL

2. WHAT IS AI ?
 Artificial Intelligence (AI) is the
simulation of human intelligence processes
by machines, especially by computer
systems.
 Various industries that uses AI:
Automobile, Pharmaceutical industries,
Marketing and manufacturing industries
and finance.

3. INTRODUCTION OF AI IN
HEALTHCARE
Artificial intelligence (AI) has made its way
into almost all aspects of our lives, whether
we know it or not. One of the industries
currently experiencing an explosion of AI
technologies is healthcare and
pharmaceutical industries.

4. AI and robotics goes hand in hand to provide us a
better lifestyle.

5. APPLICATION OF AI IN
HEALTHCARE
 Diagnostics
 Drug Discovery & Clinical Trials
 Radiotherapy and radiology
 Gene Editing
 Medication Management
 Electronic Health Record (EHR)

6. CURRENT SCENARIO
 Merck partnership with Numerate in
march 2012 focusing on generating
novel and small drug molecules for
unnamed cardiovascular disease target.
 In December 2016 Pfizer and IBM
announced partnership to accelerate
drug discovery in immunooncology.
 Many big pharmaceutical industries
began investing in AI in order to
develop better diagnostics to identify
drug targets and to design new drugs
and products.

7. PERSONALIZED TREATMENT
 Micro biosensors and devices, mobile
apps with more sophisticated health
measurements and remote monitoring
capabilities, these data can further
be used for R&D
 DermCheck: an app available in Google
play store which sent images to
dermatologists.

8. ADVANTAGES OF AI IN
CLINICAL RESEARCH
 Cutting cost
Improving trail quality
Reducing trail time by half
Finding biomarkers and gene signatures
that cause diseases
Recruiting trail patients in minutes
Reading volumes of texts and data in
seconds
On the verse of discovering new
diagnostics tools for treatments for
cancer and other chronic diseases.

9. CLINICAL TRIAL RESEARCH
 Advanced predictive analysis in identifying
candidates for clinical training
 Remote monitoring and real time data access
for any sign of harm or death to participants
 Finding best sample sizes for increased
efficiency; addressing and adapting to
differences in sites for patient recruitments;
using electronic medical records to reduce
data errors.
 Machine learning: to shape, direct clinical
trails

10. EPIDEMIC OUTBREAK
PREDICTION
To predict malaria outbreaks
from data like temperature,
average monthly rainfall, total
number of positive cases etc
ProMED- mail is a internet
based reporting program for
monitoring emerging diseases
and providing outbreaks reports.

11. RADIOLOGY AND
RADIOTHERAPY
 Google's DeepMind Health is
working with University college
London hospital(UCLH) to develop
machine learning algorithms and
capable of detecting differences
in healthy and cancerous
tissues.

12. SMART ELECTRONIC HEALTH
RECORDS
AI to help diagnosis, clinical
decisions and personalized
treatment suggestions
Handwriting recognition and
transforming cursive or other
sketched handwriting into digital
characters.