Artificial Intelligence Track

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Workshops

AIW01: From Data Analytics to Artificial Intelligence in Radiation Medicine      |      Fee: SR 150

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Registration Fee: SR 150
Workshop Code: AIW01
Date & Time/Duration: Feb 09, 2020, 08:15-9:30 / 75 min
Venue: Alfaisal University
Maximum Capacity: 50
Coordinator: Lina Alfantoukh, PhD
Instructors: Lina Alfantoukh, PhD; WS Assistant Maha Aleid, PhD
Target Audience: All individuals who are interested in AI for radiation medicine.
Prerequisites (if applicable): Basic knowledge of Radiation Medicine.

Workshop Description: Transforming radiation data to precision medicine with Artificial Intelligence.

Learning Objectives:
  • Learning the concept of Data Analytics.
  • Understanding the relationship between the Machine Learning and Artificial Intelligence.
  • Understanding the required phases to build Artificial Intelligence applications.
  • Listing the current Artificial Intelligence applications in Radiation Medicine.

AIW02: Basic Imaging Processing and artificial intelligence in Radiology (Hands-on)      |      Fee: SR 200

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Registration Fee: SR 200
Workshop Code: AIW02
Date & Time/Duration: Sunday; February 9, 2020; 9:00-12:00
Venue:Alfaisal University
Maximum Capacity: 20-30
Coordinator:
Instructors: Dr.Metab Alkubeyyer
Target Audience: Physicians, physicists, engineers, technologists, students, researchers, oncologist, computer scientist.

Prerequisites (if applicable):
Bring your own fully charged laptop and download the following free softwares:
Workshop Description: Open source software has had an expanding role in the development of image analysis routines for radiology research applications. Compared to commercial proprietary software, open source software is often more adaptable and economical. The purpose of this workshop is to familiarize participants with the features of ImageJ/FIJI , an open source image processing program The utility of ImageJ for performing automated image filtration, segmentation and registration tasks that are repeatable and can be tailored using information on the DICOM headers of images will be discussed. Case studies using clinical images will be used to demonstrate the capabilities of ImageJ. These demonstrations will also show how the capabilities of this software can be expanded using macros scripts and plug-ins (FIJI only). A quick demonstration of WEKA (https://www.cs.waikato.ac.nz/ml/weka/ ) a machine learning package embedded in FIJI.

Learning Objectives:
Upon completion of this workshop, attendees should be able to:
  • Open DICOM images and check DICOM tags
  • Apply filters (noise removal, enhance edges)
  • Enhance Image contrast.
  • Extract some imaging features & measurement ( example texture analysis).
  • Apply artificial intelligence & machine learning algorithm for segmentation or predicting cancer.
  • Export segmentation as STL which can be used for 3D printing or sent as new series for radiologists.

AIW03: Introduction To AI in Medicine (Show & Tell)      |      Fee: SR 150

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Registration Fee: SR 150
Workshop Code: AIW03
Date & Time/Duration: Sunday February 9th, 2020
Venue: Alfaisal University
Maximum Capacity: 50
Coordinator:
Instructors: Dr. WonChul Bang, Mr. Prashant Shah, Dr. Jay Hah, Dr. Seungwook Yang
Target Audience: Physicians, physicists, engineers, technologists, students, researchers, oncologist, computer scientist.
Prerequisites (if applicable): No background required

Workshop Description: This workshop will introduce the Artifical Intelligence in medicine and describe some new technical breakthroughs in the processing powers to analyze big data in fast and efficient performance.

Learning Objectives:
Upon completion of this workshop, attendees should be able to:
  • To understand the basics of AI
  • To understand the need of AI in medicine
  • To understand the technical and clinical aspects of implementing AI in hospitals

Program

Sunday, 09 February 2020
Workshops (8:15 AM - 5:00 PM)
Time
Title
Instructor
Max #
08:15-9:30 WS 1: From Data Analytics to Artificial Intelligence in Radiation Medicine Dr. Lina Alfantoukh 50
09:15-12:15 WS 2: Basic Imaging Processing and image segmentation using artificial intelligence in Radiology Dr. Meteb Alkubeyyer 20-30
16:00-17:30 WS 3: Introduction To AI in Medicine (Show & Tell)
  • How we can best assist the radiologists with AI - Dr. WonChul Bang
  • AI applications in medical Imaging with clinical evidences in ultrasound -Dr. Jay Hah
  • Accelerating AI-based Medical Imaging on Intel Architecture -Mr. Prashant Shah
 50
17:30-17:45 Chat With AI Experts All 50

Monday, 10 February 2020
Time
Title
Speakers
CEC Session
8:00-8:10 Welcome to AI Track - Program Preview Dr. Ghashgary
8:10-8:35 Basic Terminology: Artificial Intelligence, Machine Learning and Data Analytics Dr. Lina Alfantoukh
8:35-9:00 KFSH&RC Disease Registries and AI Implementations Dr. Maha AL-Eid
9:00-9:25 Big Data 2.0 (Cognitive Computing) Dr. Faris Abumelha
9:25-9:30 Discussion All
9:30-10:00
Coffee Break
12:00-13:30
Prayer Time & Lunch Break
Scientific Session
13:30-14:10 Preparing your Radiology Practice and IT Department for Big Data and AI Prof. Paul Chang
14:10-14:35 The AI Integration into the clinical workflow. The next big wave in AI Dr. Michael Perkuhn
14:35-15:00 Review RSNA critical guidelines for algorithm assessment Dr. Ty Vachon
15:00-15:25 AI applications in medical Imaging with clinical evidences in digital radiography Dr. Seungwook Yang
15:25-15:30 Discussion All
15:30-16:00
Prayer and Coffee Break
16:00-16:40 Clinical Research: AI Brain Cancer Research from Pre-operative tumor segmentation to outcome prediction Dr. Michael Perkuhn
16:45-17:15/td> Protecting Healthcare Artificial Intelligence Systems: Cybersecurity Standpoints Dr. Lina Alfantoukh
17:15-17:30 Discussion All

Tuesday, 11 February 2020
Time
Title
Speakers
CEC Session
8:00-8:10 Welcome to AI Track - Program Preview Dr. Ghashgary/Nobah
8:10-8:40 Applied Healthcare Intelligence: Governance & Use Cases Dr. Ahmad Abusalah
8:40-9:20 AI in Medical Imaging Mark O'Herlihy
9:20-9:30 Discussion All
9:30-10:00
Coffee Break
12:00-13:30
Prayer Time & Lunch Break
Scientific Session
13:30-14:10 Artificial Intelligence and Machine Learning in Radiology: A Reality Check Prof. Paul Chang
14:10-14:45 Distribution of AI models from 2015 to today to tomorrow Dr. Ty Vachon
14:45-15:15 DIAM (Key Factor for Success in Radiology) Dr. Munif Eid
15:15-15:30 Discussion All
15:30-16:00
Prayer and Coffee Break
16:00-16:30 Clinical Chalenges for AI in Oncology Prof. Evis Sala
16:30-16:55 Radiation Knowledge Initiative: Crowd Sourcing Radiotherapy Plans for ML Mr. Ahmad Nobah
16:55-17:20 The moment of adaptive intelligence is now Dr. Machael Stead
17:20-17:30 Discussion All

Wednesday, 12 February 2020
Time
Title
Speakers
Abstract Session
8:00-8:10 Introduction Mr. Ahmad Nobah
8:10-8:20 Abstract 1
8:20-8:30 Abstract 2
8:30-8:40 Abstract 3
8:40-8:50 Abstract 4
8:50-9:10 Abstract 5
9:10-9:20 Abstract 6
9:20-9:30 Discussion All
9:30-10:00
Coffee Break
12:00-13:30
Prayer Time & Lunch Break

Scientific Tracks