Dr Ida Pu

Publications and research outputs

Book

• Fundamental Data Compression Pu, Ida . 2006. Fundamental Data Compression. 0-7506-6310-3: Elsevier.

Book Section

• Efficient algorithms for noise propagation in diffusion tensor imaging Pu, Ida ; and Shen, Y.. 2009. Efficient algorithms for noise propagation in diffusion tensor imaging. In: Joseph Chan; Jacqueline Daykin and M. Sohel Rahman, eds. London Algorithmics 2008: Theory and Practice: (Texts in Algorithmics). London: College Publications, pp. 1-21. ISBN 978-1-904-98797-0

Article

• Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks Pu, Ida ; Stamate, Daniel ; and Shen, Yuji. 2014. Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks. Journal of Discrete Algorithms, 24, pp. 59-67. ISSN 1570-8667
• Quantification of venous vessel size in human brain in response to hypercapnia and hyperoxia using magnetic resonance imaging Shen, Yuji; and Pu, Ida . 2013. Quantification of venous vessel size in human brain in response to hypercapnia and hyperoxia using magnetic resonance imaging. Magnetic Resonance in Medicine, 69(6), pp. 1541-1552. ISSN 0740-3194
• Gray matter nulled and vascular space occupancy dependent fMRI response to visual stimulation during hypoxic hypoxia Shen, Yuji; Ho, Yi-Ching L.; Vidyasagar, Rishma; Balanos, George; Golay, Xavier; Pu, Ida ; and Kauppinen, Risto A.. 2012. Gray matter nulled and vascular space occupancy dependent fMRI response to visual stimulation during hypoxic hypoxia. NeuroImage, 59(4), pp. 3450-3456. ISSN 1053-8119

Conference or Workshop Item

• Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort Musto, Henry ; Stamate, Daniel ; Pu, Ida ; and Stahl, Daniel. 2023. 'Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort'. In: Computational Collective Intelligence. ICCCI 2023.. Budapest, Hungary 27–29 September 2023.
• A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease Musto, Henry ; Stamate, Daniel ; Pu, Ida ; and Stahl, Daniel. 2022. 'A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease'. In: 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Pasadena, CA, United States 13-16 December 2021.
• Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification Ermaliuc, Miha ; Stamate, Daniel ; Magoulas, George D.; and Pu, Ida . 2021. 'Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification'. In: International Conference on Engineering Applications of Neural Networks. Halkidiki, Greece 25–27 June 2021.