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Marios S. Pattichis
University of New Mexico
289Publications
25H-index
2,989Citations
Publications 289
Newest
Published on Feb 1, 2019in Solar Physics 2.58
S. Wallace1
Estimated H-index: 1
(UNM: University of New Mexico),
C. N. Arge1
Estimated H-index: 1
(GSFC: Goddard Space Flight Center)
+ 2 AuthorsC. J. Henney17
Estimated H-index: 17
(AFRL: Air Force Research Laboratory)
Over the solar-activity cycle, there are extended periods where significant discrepancies occur between the spacecraft-observed total (unsigned) open magnetic flux and that determined from coronal models. In this article, the total open heliospheric magnetic flux is computed using two different methods and then compared with results obtained from in-situ interplanetary magnetic-field observations. The first method uses two different types of photospheric magnetic-field maps as input to the Wang–...
1 Citations Source Cite
Published on Jan 1, 2019in arXiv: Learning
Alvaro E. Ulloa Cerna , Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico)
+ 5 AuthorsBrandon K. Fornwalt13
Estimated H-index: 13
We present an interpretable neural network for predicting an important clinical outcome (1-year mortality) from multi-modal Electronic Health Record (EHR) data. Our approach builds on prior multi-modal machine learning models by now enabling visualization of how individual factors contribute to the overall outcome risk, assuming other factors remain constant, which was previously impossible. We demonstrate the value of this approach using a large multi-modal clinical dataset including both EHR d...
Published on Jan 1, 2019in IEEE Journal of Biomedical and Health Informatics 3.85
A. Panayides11
Estimated H-index: 11
(UCY: University of Cyprus),
Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico)
+ 3 AuthorsConstantinos S. Pattichis34
Estimated H-index: 34
(UCY: University of Cyprus)
Precision medicine promises better healthcare delivery by improving clinical practice. Using evidence-based sub-stratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways towards optimizing care for the specific needs of each patient. The wealth of today's healthcare data, often characterized as big data, provides invaluable resources towards new knowledge discovery that has the potential to advance precision ...
1 Citations Source Cite
Published on Jan 1, 2019
Carlos LopezLeiva2
Estimated H-index: 2
(UNM: University of New Mexico),
Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico),
Sylvia Celedón-Pattichis4
Estimated H-index: 4
(UNM: University of New Mexico)
Whilst Science, Technology, Engineering and Mathematics (STEM) interdisciplinary teaching and learning in the USA K-12 education still needs greater promotion, middle school students demonstrated that they can, using low-cost, single board computers that promote the teaching of computer science (in this case Raspberry Pis), successfully engage with computer programming of digital images and videos. The context for these students’ engagement was the Advancing Out-of-School Learning in Mathematics...
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Published on May 15, 2019in arXiv: Learning
Alvaro Ulloa4
Estimated H-index: 4
,
Linyuan Jing8
Estimated H-index: 8
+ 13 AuthorsJoseph B. Leader9
Estimated H-index: 9
Predicting future clinical events helps physicians guide appropriate intervention. Machine learning has tremendous promise to assist physicians with predictions based on the discovery of complex patterns from historical data, such as large, longitudinal electronic health records (EHR). This study is a first attempt to demonstrate such capabilities using raw echocardiographic videos of the heart. We show that a large dataset of 723,754 clinically-acquired echocardiographic videos (~45 million ima...
Published on Oct 1, 2018
Wenjing Shi (UNM: University of New Mexico), Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico)
+ 1 AuthorsCarlos LopezLeiva2
Estimated H-index: 2
(UNM: University of New Mexico)
We introduce a new method to detect student group interactions in collaborative learning videos. We consider the following video activities: (i) human to human, (ii) human to others, and (iii) lack of any interaction. The system uses multidimensional AM-FM methods to detect student faces, hair, and then use the results to detect possible interactions. We use dynamic graphs to represent group interactions within each video. We tested our methods with 15 videos and achieved an 84% accuracy for stu...
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Published on Oct 1, 2018 in ICIP (International Conference on Image Processing)
Cesar Carranza5
Estimated H-index: 5
(PUCP: Pontifical Catholic University of Peru),
Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico),
Daniel Llamocca8
Estimated H-index: 8
(UR: University of Rochester)
The Discrete Periodic Radon Transform (DPRT) has many important applications in reconstructing images from their projections and has recently been used in fast and scalable architectures for computing 2D convolutions. Unfortunately, the direct computation of the DPRT involves $O(N^{3})$ additions and memory accesses that can be very costly in single-core architectures. The current paper presents new and efficient algorithms for computing the DPRT and its inverse on multi-core CPUs and GPUs. The ...
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Published on Jul 1, 2018in IEEE Journal of Biomedical and Health Informatics 3.85
Zinonas C. Antoniou5
Estimated H-index: 5
(UCY: University of Cyprus),
A. Panayides11
Estimated H-index: 11
(UCY: University of Cyprus)
+ 3 AuthorsMarios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico)
The wider adoption of mobile Health video communication systems in standard clinical practice requires real-time control to provide for adequate levels of clinical video quality to support reliable diagnosis. The latter can only be achieved with real-time adaptation to time-varying wireless networks’ state to guarantee clinically acceptable performance throughout the streaming session, while conforming to device capabilities for supporting real-time encoding. We propose an adaptive video encodin...
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Published on Apr 1, 2018
Abigail Ruth Jacoby (UNM: University of New Mexico), Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico)
+ 1 AuthorsCarlos LopezLeiva2
Estimated H-index: 2
(UNM: University of New Mexico)
Human activity classification remains challenging due to the strong need to eliminate structural noise, the multitude of possible activities, and the strong variations in video acquisition. The current paper explores the study of human activity classification in a collaborative learning environment.This paper explores the use of color based object detection in conjunction with contextualization of object interaction to isolate motion vectors specific to each human activity. The basic approach is...
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Published on Apr 1, 2018
Wenjing Shi (UNM: University of New Mexico), Marios S. Pattichis25
Estimated H-index: 25
(UNM: University of New Mexico)
+ 1 AuthorsCarlos LopezLeiva2
Estimated H-index: 2
(UNM: University of New Mexico)
The paper introduces the problem of robust head detection in collaborative learning environments. In such environments, the camera remains fixed while the students are allowed to sit at different parts of a table. Example challenges include the fact that students may be facing away from the camera or exposing different parts of their face to the camera. To address these issues, the paper proposes the development of two new methods based on Amplitude Modulation-Frequency Modulation (AM-FM) models...
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