The Institute of Business Administration Karachi and the Department of Medicine of the Aga Khan University signed a memorandum of understanding to provide a fully-funded research training opportunity in data science and non-communicable diseases to four candidates.
The MoU-signing ceremony was held at the AKU and Dr S Akbar Zaidi, executive director, IBA; and Sulaiman Shahbuddin, President, AKU, graced the event as chief guests.
Dr Shakeel Khoja, dean, School of Mathematics and Computer Science, IBA, and Dr Adil Haider, dean, Medical College, AKU, signed the agreement on behalf of their respective institutions. The collaboration aims to enable and support aspirational data science students interested in the research of NCDs.
The selected students will be fully funded for their Master’s in Data Science from SMCS, IBA, and will be provided with the opportunity to work as a paid research instructor for two years at the Department of Medicine, AKU. Furthermore, the programme includes mentorship by the IBA, AKU and Duke University Faculty.
The IBA team included Dr Tariq Mahmood, professor and programme coordinator, MS Computer Science and MS Data science programs; Dr Shahid Hussain, chairperson, Computer Science Department; and Dr Sajjad Haider, professor, Computer Science Department, AKU, was represented by Dr Zainab Samad, Ibn-e-Sina, professor and chair, Department of Medicine and director, CITRIC Health Data Science Centre; Dr Adil Haider, dean, Medical College, and other faculty members.
The event commenced with opening remarks by Dr Zainab Samad and Dr Gerald Bloomfield, associate professor, Department of Medicine and Global Health Institute, Duke University.
A panel discussion moderated by Dr Sarmad ensued and included the following speakers: Dr Sajjad Haider, professor, Computer Science Department, IBA; Dr Zulfiqar Bhutta, distinguished university professor, Department of Paediatrics & Child Health, AKU; Dr John Bartlett, professor of medicine, Global Health and Nursing, Duke University; Dr Ayesha Kamal, professor of neurology, AKU; and Dr Ayesha Almas, associate professor of medicine, AKU.
Dr Haider elaborated that the collaboration would enable academics from the AKU and the IBA to investigate the applications of existing machine-learning algorithms for healthcare problems such as patient stay prediction, the possibility of readmission, and early warning systems to predict patient risk at an early stage. Additionally, the joint effort would also focus on the application of computer vision techniques on medical images and text analytics techniques on clinical notes and radiologist reports. This collaboration would also provide an avenue to develop novel methods for explainable Artificial Intelligence in the health domain.
Addressing the audience, Dr Zaidi commended the AKU for organising an excellent event and for playing an integral role in this collaboration between IBA, AKU and Duke University to train researchers who can understand and contribute towards suggesting and developing low-cost solutions to NCDs. He also said that this collaboration will bring great research opportunities for his colleagues.
Sharing his views, Dr Khoja said: “This is a unique academic partnership in Pakistan between the IBA and the AKU, where academics will work in their own domains to carry out research in order to solve local problems and challenges.”
Expressing his appreciation, Mr Shahbuddin thanked Dr Zaidi for gracing the event with his presence. Furthermore, he said that as a proud IBA alumnus, he was delighted at this collaboration between the two finest institutes, the AKU and the IBA, which have come together to deliver this project on data science and building capacities for research in NCDs in Pakistan.
Speaking about the programme structure, Dr Tariq Mahmood said, “The exact method through which this programme will be executed is through first identifying the NCD health indicators. Then we are going to create problem statements and research questions pertaining to the improvement of these health indicators. We will then convert these problems to formal projects to be executed in the MSDS programme as MS theses, MS projects or course projects. Furthermore, we will strive for maximum performance through aggressive hands-on activities in data science skills.”
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