Dr. Sangeeta PPT fro STTP 18 Jan.pptx

Day-III Session on “Emerging Technologies of Data Science and Artificial Intelligence”
Presented By:
Dr. Sangeeta Tripathi
20-Feb-23 1

g
Contents
 Introduction to AI
 Real Life A.I. Examples
 AI Timeline
 Machine Learning
 Deep Learning
 The Future of A.I.
 AI in Healthcare
 Biomedical Engineering
 Nano- Technology
 How AI, Data Science and ML Serving the Humanity
 Artificial Intelligence Application in Cyber crime
 How to protect yourself against cybercrime
 Top New Technology Trends, 2023…
20-Feb-23 2

What do you think
Artificial Intelligence
is?
20-Feb-23 3

Artificial
Intelligence in
Movies
In movies, robots are
able to talk, think,
have emotions, and
make decisions just
like humans
20-Feb-23 4

What is Artificial
Intelligence?
Artificial Intelligence is the theory and
development of computer systems that are
able to perform tasks that would required
human intelligence.
Examples of these tasks are visual
perception, speech recognition, decision-
making and translation between languages
“The science and engineering of making intelligent machines,
especially intelligent computer programs”. – According to the
father of Artificial Intelligence, John McCarthy
20-Feb-23 5

Real Life A.I.
Examples
❏ Self Driving Cars
❏ Google Maps - traffic
predictions are
satellite-based
❏ Video Games
❏ Movie
Recommendations
❏ Sports Strategies -
Designing strategy for
a multi-player team
sports is quite a
difficult task for AI
Summing up
AI is everywhere, and it could be
harnessed to help solve major
challenges whether business or
personal. It has already brought
dramatic changes in the whole world
with new inventions and technology
advancements, working towards
creating a smarter, more cognitive
tomorrow.
20-Feb-23 6

AI timeline
20-Feb-23 7

As we are totally surrounded by machines and
computer systems, this gave humans a general
thought like “Can a machine think and behave
like humans do? “. Though this was a general
thought, its curiosity leads to the development
of artificial intelligence (AI).
Philosophy of AI
20-Feb-23 8

Types of Artificial
Intelligence (AI)
20-Feb-23 9

Types of Artificial
Intelligence (AI)
Weak AI
AI types
Strong AI
20-Feb-23 10

Weak A.I
Weak artificial intelligence (weak AI), also
known as narrow AI, is artificial intelligence that
is focused on one narrow task. Weak AI is
defined in contrast to either strong AI (a
machine with sentience and mind or artificial
general intelligence (a machine with the ability
to apply intelligence to any problem, rather than
just one specific problem.
20-Feb-23 11

Strong A.I.
A machine with strong A.I.
is able to think and act
just like a human. It is
able to learn from
experiences.
Since there are no real life
examples of strong A.I.
yet, the best
representation would be
how Hollywood portrays
robots.
20-Feb-23 12

Machine
Learning
An application of
ArtificialIntelligence
that gives machines
the abilityto learn
and improve without
the help of humans
or new programming.
Machine
Learning
AI
20-Feb-23 13

Deep Learning
Deep learning (also
known as deep structured
learning or
hierarchical learning) is
part of a broader family
of machine
learning methods based
on learning data
representations, as
opposed to task-specific
algorithms. Learning can
be supervised, semi-
supervised or
unsupervised.
20-Feb-23 14

Deep
Learning
Artificial intelligence is
the broader concept that
consists of everything
from Good Old-
Fashioned AI (GOFAI) all
the way to futuristic
technologies such
as deep learning. ... The
narrow intelligence AI
machines can perform
specific tasks very well,
sometimes better than
humans — though they
are limited in scope.
20-Feb-23 15

The Turing Test
Inthe1950sAlanT
uringcreated
theT
uringT
estwhichisusedto
determinethelevelof inteligenceof
acomputer
.
A computer program
mimicked human
conversation so well that it
was mistaken for a real live
human
but “machine intelligence”
still has a long way to go
20-Feb-23 16

The Turing Test Measures
Something, But It’s Not
“Intelligence”
Some people disagree
with the Turing Test. They
claim it does not actually
measure a computer's
intelligence.
20-Feb-23 17

The Future of
A.I.
★ Military Bots
★ The perfect lawyer
★ Music
★ Business
★ Healthcare
★ Nano-robotic
20-Feb-23 18

Benefits of A.I.
The most important purpose
of A.I. is to reduce human
casualties in
➔ wars
➔ Dangerous Workspaces
➔ Car Accidents
➔ Natural Disasters
➔ Healthcare
Or to just make everyday
life easier by helping with
tasks such as:
➔ Cleaning
➔ Shopping
➔ Transportation
20-Feb-23 19

• AI would have a low error rate
compared to humans, if coded
properly.
• They would have incredible
precision, accuracy, and speed.
• They won't be affected by
hostile environments, thus
able to complete dangerous
tasks, explore in space, and
endure problems that would
injure or kill us.
20-Feb-23 20

How to take advantage
of AI
Business need to overcome the trust and bias
issues surrounding AI by achieving an effective and
successful implementation that makes it possible
for everyone to benefit.
Governments must ensure that gains from AI
are shared widely across society to prevent social
inequality between those affected and unaffected
by these developments. For example, this could be
through increased investment into training.
 With the additional cost-savings from
implementing AI systems, employers should also
focus on up-skilling their current employees.
20-Feb-23 21

AI in
Healthcare
Artificial intelligence (AI) in healthcare
is the use of algorithms and software
to approximate human cognition in the
analysis of complex medical data.
Specifically, AI is the ability for
computer algorithms to approximate
conclusions without direct human
input.
20-Feb-23 22

Medical image processing
Breast cancer analysis, (sonar, MRI, fMRI,
CT)
Liver fibrosis and tumour analysis (biopsy,
MRI, CT)
Medical image annotation
Computer based Cell blood disorder
Problems:
- Breast Cancer Case
- Liver Fibrosis – HCV
- Content-based image retrieval
-Formal Concept Analysis (visualize
(rule based))
Biomedical Engineering
20-Feb-23 23

Nano-
technology
Artificial IntelligenceIntersects
with Nanotechnology
20-Feb-23 24

NanoTechnology
A truly multidisciplinary field
Artificial
Intelligence
Intersects with
Nanotechnology
20-Feb-23 25

Nanorobots can be used in blood cell to detect
pathogens:
Intersects with
Nanotech
20-Feb-23 26

Elkhosht: Nanotechnology Center at Cairo University Plays
Effective Role in Industry Development and Economy Service
Artificial Intelligence Intersects with Nanotechnology
20-Feb-23 27

Breast Cancer Case
According to the USA National Cancer Institute
report:
Breast cancer is the leading cause of cancer deaths in
women today and it is the most common type of cancer in
women.
Each year about 180,000 women in the United States
develop breast cancer, and
About 48,000 lose their lives to this disease.
It is also reported that a woman's lifetime risk of
developing breast cancer is one in eight.
Currently, digital mammography is one of the most
promising cancer control strategies in earliest stages.
A novel approach for detection of breast cancer at an early
stage using digital image processing techniques
Breast cancer screening is used to identify breast cancer
in women who have no physical symptoms. It is hoped
that finding breast cancer early will enable women to
undergo less invasive treatments, with better outcomes.
20-Feb-23 28

Thermography
Thermography is a test that detects
and records temperature changes on
the surface of the skin.
Digital infrared thermal imaging
(DITI), a type of thermography used in
the screening of breast cancer, uses an
infrared thermal camera to take a picture
of the areas of different temperature in the
breasts. The camera displays these
patterns as a sort of heat map.
Computer-aided analysis for breast cancer detection
in thermography
20-Feb-23 29

Blood cell disorders
Developing a Computer-based
What Are Blood Cell Disorders
A blood cell disorder is a condition in which
there’s a problem with your red blood cells,
white blood cells, or the smaller, circulating
cells called platelets, which are critical for clot
formation. All three cell types form in the bone
marrow, which is the soft tissue inside your
bones. Red blood cells transport oxygen to your
body’s organs and tissues. White blood cells
help your body fight infections. Platelets help
your blood to clot. Blood cell disorders impair
the formation and function of one or more of
these types of blood cells.
20-Feb-23 30

Computer-based system
Perform an accurate and consistent blood
cell count automatically
Generate blood count reports based on
standard routine
Diagnose the blood diseases automatically,
efficiently and accurately
Detect shapes of the abnormal red blood
cells automatically
Separate overlapped cells from red blood
cells
20-Feb-23 31

Developing a Computer-based
Normally, people produce about 100 billion white
blood cells a day. The number of white blood cells in
a given volume of blood is expressed as cells per
microliter of blood.
The total white blood cell count normally ranges
between 4,000 and 11,000 cells per microliter.
The proportion of each of the five major types of
white blood cells and the total number of cells of
each type in a given volume of blood can also be
determined through laboratory tests.
Leukopenia, a decrease in the number of
white blood cells to fewer than 4,000 cells per
microliter of blood, frequently makes people
more susceptible to infections.
Leukocytosis, an increase in the number of
white blood cells to more than 11,000 cells per
microliter of blood, is often caused by the
normal response of the body to help fight an
infection
20-Feb-23 32

Hepatitis C Virus in Egypt -HCV
⚫ The World Health Organization has
decleared hepatitis C a global health
problem, with approximately 3% of
the world’s population (roughly 170-
200 million people) infected with
HCV.
⚫ Egypt has one of the highest
prevalence rates of the C virus in the
world
⚫ In Egypt the situation is quite worse.
14.7 % infected with Hepatitis C
20-Feb-23 33

Liver Fibrosis
⚫ Stage 0 No fibrosis (fatty liver)
⚫ Stage 1 Portal expansion with fibrosis (<1/3 area)
⚫ Stage 2 Bridging fibrosis (>1/3)
⚫ Stage 3 Marked bridging fibrosis or early cirrhosis (
no reason for tissue conversion)
⚫ Stage 4 Definite cirrhosis (<50% of biopsy fibrosis)
⚫ Stage 5 Definite cirrhosis (>50% of biopsy fibrosis)
Challenges: distinguish between the late fibrosis stage
and tumor Good segmentation techniques/features-
based/classifier/
extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-
occurrence matrix based on ultrasound images =========== Classification problem
20-Feb-23 34

Fibro Scan – Avoid liver
biopsy
Acombination of blood test and
fibroscan for accurate non-invasive
diagnosis of liver fibrosis stages in
chronic hepatitis C.
Fibroscan for assessing liver fibrosis
Liver fibrosis identification based on ultrasound images
20-Feb-23 35

Content-based Medical Image
Retrieval
Query Image
Extract Features
(Primitives)
Image
Database
Features Database
Similarity
Measure
Matched
Results
Relevance
Feedback
Algorithm
Content-based image retrieval (CBIR) makes use of image features, such
as color and texture, to index images with minimal human intervention.
20-Feb-23 36

Heart Sound:
Recognition and
Diagnosis
Biometric
Machine learning and swarms for
feature extractions
20-Feb-23 37

How AI, Data
Science and ML
Serving the
Humanity
20-Feb-23 38

20-Feb-23 39

Predictive Analytics in Healthcare
 Healthcare analytics is important.
 Lack of information - condition can get worse.
 Information collection should be efficiently.
To generate the predictive analytics model
Data Science makes predictions on the condition of the patient
Data-blood pressure, body temperature to sugar level , that data utilized to analyzed
to search for patterns and correlations in it.
This process tries to identify the symptoms of a disease, the stages of the disease,
the extent of damage, and many more.
Therefore, predictive analytics is a very useful technique and it plays a major role in
the healthcare industry.
20-Feb-23 40

The major benefits of predictive analytics in healthcare are given
below:
 management of chronic diseases.
 It efficiently monitors and analyzes the
demand for pharmaceutical logistics.
 It predicts a patient’s condition and suggests
preventive measures.
 It provides faster documentation of hospital
data.
 It helps in efficiently utilizing doctors and
other resources for the benefit of the
maximum number of patients.
 It predicts the future medical crises of a
patient.
 Thus, the application of Data Science
in healthcare in the form of predictive
analytics is proving itself to be of great use.
20-Feb-23 41

20-Feb-23 42

Data Collection for Peter
20-Feb-23 43

AI-Training Model for Medical- Brisbane Model for Peter (Patient suffering
from Cancer)
20-Feb-23 44

AI-Training Model for Medical
20-Feb-23 45

20-Feb-23 46

20-Feb-23 47

Drug Research
20-Feb-23 48

Data Science in Genomics
20-Feb-23 49

Few Tools used
The tools used in the research of genomics are:
MapReduce: MapReduce helps in processing huge amounts of genetic data. With the help
of MapReduce, the genetic sequences can be processed in lesser time.
SQL: SQL helps in the retrieval of the genomic data from various databases and also helps in
the computation of this data.
Galaxy: It is a GUI-based application used for biomedical research. To perform research on
genomes, we can do specific operations using Galaxy.
Bioconductor: Bioconductors are used for the analysis of the genetic data.
Having knowledge of how DNA cells respond to a particular drug for a patient, doctors can
perform the treatment efficiently. The useful insights into the genetic structure help them
make effective strategies to cure a disease for a particular patient.
20-Feb-23 50

Virtual Assistance
20-Feb-23 51

Future of Data Science in Healthcare
Basically, there are four factors leading to rapid improvement in the healthcare industry:
 Technological advancements
 Digitalization
 Need for reducing treatment costs and duration
 Need for handling large population
20-Feb-23 52

Some LIVE examples of Data Science, AI across the Globe
AICure (New York City) Patient-oriented
Uses video, audio, and behavioral data to
better understand the connection between
patients, disease and treatment.
20-Feb-23 53

Aidence (Amsterdam, The
Netherlands) Clinician-
oriented
AI for radiologists: improving
diagnostics for the
treatment of lung cancer
https://www.aidence.com
20-Feb-23 54

g
Application in
Cybercrime: Review
and Open Problems
20-Feb-23 55

Cyber Security
Cyber security is the body of technologies, processes and practices designed to protect
networks, computers, programs and data from attack, damage or unauthorized access. In
a computing context, security includes both cyber security and physical security.
ML + Data Analytics + Cyber Security
 Automate the detection and prevention of attacks
India is the second-biggest target of cyber criminals in Asia-Pacific in 2020: IBM(India ranked second after
Japan in attack by cyber criminals in Asia-Pacific in 2020, was stated in an IBM report released recently.)
20-Feb-23 56

In 2020 , study of European Police agency
Europol and security provider
Trend Micro, reported that AI are
already being used by cybercriminals…
According to Accenture’s State of Cyber security Resilience 2021 report, security
attacks increased 31% from 2020 to 2021.
20-Feb-23 57

20-Feb-23 58
Cybersecurity threats are constantly evolving in today’s digital age. The increasing use of
artificial intelligence (AI) in cyber-attacks has been one of the most significant developments
in recent years. As AI technology advances, attackers use it to launch more sophisticated and
effective attacks. These AI-powered cybersecurity threats are a growing concern for
organizations and individuals alike, as they can evade traditional security measures and cause
significant damage. In this article, we will explore the top five AI-powered cybersecurity
threats.
Advanced Persistent Threats (APTs): A sophisticated, sustained cyberattack known as an
advanced persistent threat (APT) occurs when an intruder enters a network undetected and
stays there for a long time in order to steal sensitive data. They frequently involve the use of
artificial intelligence to avoid detection and target specific organizations or individuals.
Deepfake attacks: These employ artificial intelligence-generated synthetic media, such as
videos or images, to impersonate real people and carry out fraud or disinformation
campaigns.
AI-powered malware: Malware that uses AI has been taught to think for itself, adapt its
course of action in response to the situation, and particularly target its victims’ systems.
Malicious software that uses AI to avoid detection and adapt to changing environments,
makes defense more difficult.
Phishing: Using natural language processing and machine learning, attackers can create more
convincing phishing emails and messages that are designed to trick individuals into revealing
sensitive information.
DDoS attacks: Distributed Denial of Service (DDoS) attacks that use AI to identify and exploit
vulnerabilities in a network, allowing the attacker to amplify the scale and impact of the
attack.
These are some of the other AI-powered cybersecurity threats that are causing concern in the
tech industry. Cybercriminals are increasingly employing AI to carry out sophisticated and
targeted attacks on individuals and organizations. Individuals and businesses must stay
informed about the latest AI-powered cyber threats and implement robust security measures
to protect themselves.

Application in
Cyber crime
In the Europol report, disclosed -
‘generative grammar’
“These texts are then used to fuzz
the anti-spam system and adapt to
different filters in order to identify
content that would no longer be
detected by spam filters,” the report
warns.
20-Feb-23 59

Major Threats which Europol
Predicted
AI-powered software development,
which businesses are beginning to use,
could also be employed by hackers.
Europol warns that AI-based tools, which
convert natural language into code, could
lead to a new generation of ‘script
kiddies’ with low technical knowledge
but the ideas and motivation for
cybercrime
20-Feb-23 60

How to prepare for AI cybercrime
Protecting against AI-powered cybercrime will require responses at the individual,
organizational and society-wide levels.
 Employees will need to be trained to identify new threats such as deep fakes
 organizations will need to employ AI tools themselves to match the scale and
sophistication of future threats
 Europol called on governments to ensure that AI systems adhere to ‘security-by-
design’ principles, and develop specific data protection frameworks for AI.
20-Feb-23 61

How to protect yourself against cybercrime
 Keep software and operating system updated
 Use anti-virus software and keep it updated
 Use strong passwords
 Never open attachments in spam emails
 Do not click on links in spam emails or untrusted websites
 Do not give out personal information unless secure
 Contact companies directly about suspicious requests
 Be mindful of which website URLs you visit
 Keep an eye on your bank statements
20-Feb-23 62

Some Data related to Cybercrime:
Global Cyber security Market to be Propelled by Rising Volume of Data by CAGR of ~12%
During 2022 – 2031
20-Feb-23 63

Top New Technology Trends, 2023…
 Computing Power
 Smarter Devices
 Datafication
 Artificial Intelligence and Machine Learning
 Extended Reality
 Digital Trust
 3D Printing
 Genomics
 New Energy Solutions
 Robotic Process Automation (RPA)
 Edge Computing
 Quantum Computing
 Virtual Reality and Augmented Reality
 Block chain
 Internet of Things (IoT)
 5G
 Cyber Security
20-Feb-23 64

THE END
Thank You
20-Feb-23 65

Dr. Sangeeta PPT fro STTP 18 Jan.pptx

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