Technology support to predicate health. Technology defence against coronoa virus. Technglogy framework for Minjstry of Health. AI forcasting disease

1. AMIGO: COVID-19 Detection,
management, and predication system
using Artificial Intelligent Techniques

2. Hello!
I am Assoc. Prof. Dr. Mogeeb A. A. Mosleh.
For more information: google me (Mogeeb Mosleh)
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3. Challenges
Solutions
• Develop and Build up a central reliable
database for health system in Yemen.
• Development an Intelligent system to
detect, monitor, forecast COVID-19 and
any epidemic diseases in Yemen.
• Integrate efficient and appropriate
Artificial Intelligent tools to assist in
managing the crisis of COVID-19.
• Development a machine learning tools
to assist medical sectors in preventing
spreading, follow up active and
suspected cases of COVID-19.
Problems
• COVID-19 is currently most threatens for
Human lives over the World.
• Current Health System in Yemen is very
weak to detect, monitor, and forecast
COVID-19 or any epidemic diseases.
• Its nearly Impossible to Manage the crisis
of COVID-19 in Yemen.
• Governments, organizations, and Health
facilities mostly delayed or has difficulties
in taken necessary decisions or actions in
medical sectors.
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4. “Recent Researches
Reported That:
“Artificial intelligence
fights fiercely with
humans in the survival
battle against COVID-19.”
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5. How to fight COVID-19 with
Data & Artificial Intelligent
 To identify, predict and track disease
outbreaks
 Identify who is most at risk,
 Diagnose patients,
 Develop drugs faster,
 Finding existing drugs that can help
 Understand viruses better,
 Map where viruses come from.
 Robots to sterilize, deliver food &
medical supplies.
 Predict the next pandemic.
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6. Lean Canvas Business Model
▸ UNIQUE VALUE
PROPOSITION
1. Valid Data and information integrity purposes.
2. Useful for Risk reductions risks via early
detections, forecasting spreading, updating active
and passive cases,
3. Assist medical care center in classified COID-19
cases by using A.I methods with specific parameter
4. Provides reliable database (Valid and Updated)
for concern local and internationals organizations.
5. Assist system users to evaluate, estimate, and
predicate their condition if they infected with
COVID-19, which help in preventing COVID-19
Spreading.
▸ KEY METRICS
1-usability using SUS not less than 90%.
2-acuracy more than 90%.
3-speed and performance 0.02per transaction
4-Avaliability 24/7 hours for services
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▸ CUSTOMER SEGEMENTS
1. Governments offices such as Ministry of
Health.
2. Hospitals, Clinics, and medical care centers.
3. Interested organizations such as (WHO).
4. End users

7. Lean Canvas Business Model
▸ CHANNELS
Online data Communication.
for interested organizations and the Ministry of Health,
providing accurate and real information about COVID-
19 cases. Also, support medical specialist and normal
people
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▸ UNFAIRE ADVANTAGE
1. Centralized Reliable Database
2. Data mining for prediction and extrapolation using
artificial intelligent techniques.

8. Lean Canvas Business Model
▸ COST STRUCTURE
1. Survey Expenses
2. Communication expenses 200$
3. Wage expenses 2000$
4. Stationary 300$
5. Hosting expenses 300$
▸ REVENUE STREAMS
1. B2G Subscription
2. B2P
3. ads website
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9. Data Analaytics
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EndUser
03 ✔ Examine symptoms and forecasting by AI.
government
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✔ Early detection of disease spreading
✔ Make decision by AI
✔ Forcasting and ability to know statistics of covid19
cases
Medical Health stuff
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✔ Enter confirmed and suspected Covid19 cases
✔ Make decision by AI
✔ Ability Determine degree of seriousness

10. 10
1- Prof. Dr. Mogeeb A. A. Mosleh
Project Manager
PhD in Artificial Intelligent – Machine
learning
2- Prof. Dr. Murad AlDarasi
Asst. Professor – Head of
Department of Community
Medicine
3-Eng. Enass Aldahbali
Software Analyst
4-Eng. Nora Almansour
Software Development

11. A.I Model & Prototype
Centralized Cloud Database

12. A.I Model & Prototype

13. website& Prototype

14. Integrated Intelligent tools
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Follow Up, and Monitoring Confirmed
and Suspected Cases of COVID-19
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✔ Input: Confirm Cases + Suspect Cases + Extensive care
unit Sensor Data
✔ A. I. Tool: K-Means Clustering
✔ Output: Update Cases Outcome, Alert for Critical
Situations.
Forcasting spread of COVID-19
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✔ Input: Confirm Cases + Suspect Cases + Specific Parameters
(Population + Interaction behaviors + COVID-19 Spreading
Model)
✔ A. I. Tool: Deep Learning
✔ Output: Estimated Infected People + Spreading Rate
Early Detecting COVID-19 or any
Epidemic disease
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✔ Input: Central Database
✔ A.I Tools: SVM, SOM
✔ Output: Alert, Triger, Warning with (Statistical Report)
Evaluate and Predicate the Person
Health condition if infected with
COVID-19
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✔ Input: Specific Case Medical Parameters + World COVID-
19 DATA SET.
✔ A. I. Tools: Deep Learning + SOM
✔ Output: Report forecasting what will be happen if you
have COVID-19.

15.  Establish reliable database for Health system
 preventing spreading by early detection
 reduce the risk cases monitoring and controlling
confirm and suspected cases.
 identify the cases risk level which help medical
care to reduce death cases.
Impacts

16. Our process is easy
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July/2020
Execute Project
Achieving All Projects tasks and goals
Aug/2020
Project Delivery
Deliver the products to the end users.
April/2020
Business Plan
Develop Business Plan.
May/2020
Approval of Project
Approve Project Plan & Budget

17. “Ask
1. Investment
2. Mentorship
3. Licensing and policy
planning
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