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ـه1442 ةرخآلا ىدامج 226 Forum 14
م2021 رياــني

4-Days Artificial

Intelligence Bootcamp

September 13 – 16, 2020
By: Prof.Tanzila Saba - AIDA Lab, Leader
Artificial Intelligence and Data Analytics Information Systems, Computer
Lab (AIDA) at Prince Sultan University Science, Law, Architecture, Marketing,
conducted the first online instructor Software Engineering, and Applied
led practical AI Bootcamp designed for Linguistic and from different universities
working professionals and students by including Prince Sultan University, Al-
the professionally certified members. Imam University, King Saud University
This professional AI Bootcamp and Albaha university. At the end
offered 8 hours of training covered the trainees expressed the high level
the main topics in data analysis, data of satisfaction and appreciated the
visualizations, dashboards design, and knowledge and efforts of the trainers.
machine learning. After the successful AIDA lab is grateful for the cooperation
completion of the training, the trainees and support of the AIDA lab members for
were awarded the AI Bootcamp their contribution to the AI Bootcamp.
Attendance/Completion Certificate Thanks to Dr.Souad Larabi, Ms Fatima
and Appreciation Certificates were Khan, Ms Laya Kazma, Ms Saima Rashid
given to the trainers. The trainees and Ms Nermeen Hakim for delivering
were from diverse majors including the excellent hands-on trainings.

Invited Speakers at the 6th International Conference

on Fuzzy Systems and Data Mining (FSDM 2020)

November 13-16, 2020, Online Conference- Beijing, China
Written by AIDA Lab Leader, Dr.Tanzila Saba
AIDA Lab, Leader Dr.Tanzila Saba & Senior Arabia this paper, only a subset of 14 attributes are
Researcher Dr. Khaled Mohamed Almustafa Speech Title: AI in Healthcare: State of the used, and each attribute has a given set value.
(Chief Information and Technology Officer, Art, Current Trends and Future Possibilities The algorithms used K- Nearest Neighbor (K-
CITO) honored to present at the 6th Abstract: Artificial intelligence in NN), Naive Bayes, Decision tree J48, JRip, SVM,
International Conference on Fuzzy Systems healthcare has been a particularly hot Adaboost, Stochastic Gradient Decent (SGD)
and Data Mining (FSDM 2020) as the research topic in recent years. Artificial and Decision Table (DT) classifiers to show the
Invited Speakers. The main emphasis of the intelligence has come a long way since it performance of the selected classifications
conference was on Fuzzy Theory, Algorithm was first established as a field in 1956. It algorithms to best classify, and or predict, the HD
and System, Fuzzy Application, Data Mining has been playing a critical role in industries cases. Results: It was shown that using different
and Interdisciplinary fields of Fuzzy Logic for decades. AI has only recently begun to classification algorithms for the classification of
and Data Mining. The conference was take a leading role in healthcare. A recent the HD dataset gives very promising results in
featured with plenary session, including McKinsey review predicted healthcare as term of the classification accuracy for the K-NN
keynote speeches, invited speeches, oral one of the top five industries with more Dr. Khaled Almustafa, Associate Professor (K=1), Decision tree J48 and JRip classifiers
presentations and poster presentations. than 50 use cases that would involve Senior Researcher,Artificial Intelligence & with accuracy of classification of 99.7073%,
AI. This transformative technology is Data Analytics Research Lab 98.0488% and 97.2683% respectively. A feature
revolutionizing the health sectors in many Prince Sultan University, Saudi Arabia extraction method was performed using
ways, from drug development to clinical Speech Title: Prediction of Heart Disease and Classifier Subset Evaluator on the HD dataset,
research; AI has helped improve patient Classifiers’ Sensitivity Analysis and results show enhanced performance in
outcomes at reduced costs. Numerous Abstract: Background: Heart disease (HD) is term of the classification accuracy for K-NN
applications of AI such as virtual assistants, one of the most common diseases nowadays, (N=1) and Decision Table classifiers to 100% and
robotic assisted surgery, are well positioned and an early diagnosis of such a disease is a 93.8537% respectively after using the selected
to improve patient care and potentially crucial task for many health care providers to features by only applying a combination of
save lives. While there is a sense of prevent their patients for such a disease and to up to 4 attributes instead of 13 attributes for
great potential in the application of AI save lives. In this paper, a comparative analysis the predication of the HD cases. Conclusion:
in healthcare, there are also concerns of of different classifiers was performed for the Different classifiers were used and compared
privacy, accuracy, data ownership, integrity, classification of the Heart Disease dataset in to classify the HD dataset, and we concluded
Dr. Tanzila Saba, Research Professor data usability about it. This talk will highlight order to correctly classify and or predict HD the benefit of having a reliable feature selection
Artificial Intelligence & Data Analytics the current applications, future innovations cases with minimal attributes. The set contains method for HD disease prediction with using
Research Lab, Leader and possible issues of AI applications in 76 attributes including the class attribute, minimal number of attributes instead of having
College of Computer and Information healthcare. for 1025 patients collected from Cleveland, to consider all available ones.
Sciences, Prince Sultan University, Saudi http://www.fsdmconf.org/Speaker Hungary, Switzerland, and Long Beach, but in http://www.fsdmconf.org/Speaker