67 citations · 101 across the 5 of their papers we have counts for
5 papers
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991-2020)
Roohallah Alizadehsani, Mohamad Roshanzamir, Sadiq Hussain +12
Understanding data and reaching valid conclusions are of paramount importance in the present era of big data. Machine learning and probability theory methods have widespread applic…
Discovering topic structures of a temporally evolving document corpus
Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Phung +1
In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimens…
Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis
Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Phung +1
Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently l…
Using Twitter to learn about the autism community
Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Phung +2
Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision making and communication of the latest guidelines…
Hierarchical Dirichlet process for tracking complex topical structure evolution and its application to autism research literature
Adham Beykikhoshk, Ognjen Arandjelovic, Dinh Phung +1
In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimens…