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Using Kernel Methods and Model Selection for Prediction of Preterm Birth [article]

Ilia Vovsha, Ansaf Salleb-Aouissi, Anita Raja, Thomas Koch, Alex Rybchuk, Axinia Radeva, Ashwath Rajan, Yiwen Huang, Hatim Diab, Ashish Tomar,, Ronald Wapner
2016 arXiv   pre-print
We describe an application of machine learning to the problem of predicting preterm birth. We conduct a secondary analysis on a clinical trial dataset collected by the National In- stitute of Child Health and Human Development (NICHD) while focusing our attention on predicting different classes of preterm birth. We compare three approaches for deriving predictive models: a support vector machine (SVM) approach with linear and non-linear kernels, logistic regression with different model
more » ... along with a model based on decision rules prescribed by physician experts for prediction of preterm birth. Our approach highlights the pre-processing methods applied to handle the inherent dynamics, noise and gaps in the data and describe techniques used to handle skewed class distributions. Empirical experiments demonstrate significant improvement in predicting preterm birth compared to past work.
arXiv:1607.07959v2 fatcat:ejinz33bqvcijfuztgozmmtvaq

Patient-Specific Seizure Detection from Intra-cranial EEG Using High Dimensional Clustering

Haimonti Dutta, David Waltz, Karthik M. Ramasamy, Phil Gross, Ansaf Salleb-Aouissi, Hatim Diab, Manoj Pooleery, Catherine A. Schevon, Ronald Emerson
2010 2010 Ninth International Conference on Machine Learning and Applications  
Automatic seizure detection is becoming popular in modern epilepsy monitoring units since it assists diagnostic monitoring and reduces manual review of large volumes of EEG recordings. In this paper, we describe the application of machine learning algorithms for building patient-specific seizure detectors on multiple frequency bands of intra-cranial electroencephalogram (iEEG) recorded by a dense Micro-Electrode Array (MEA). The MEA is capable of recording at a very high sampling rate (30 KHz)
more » ... roducing an avalanche of time series data. We explore subsets of this data to build seizure detectors -we discuss several methods for extracting univariate and bivariate features from the channels and study the effectiveness of using high dimensional clustering algorithms such as K-means and Subspace clustering for constructing the model. Future work involves design of more robust seizure detectors using other features and non-parametric clustering techniques, detection of artifacts and understanding the generalization properties of the models.
doi:10.1109/icmla.2010.119 dblp:conf/icmla/DuttaWRGSDPSE10 fatcat:rtu22cq25jgrhdp6jcd36on2ca

A case-study on learning from large-scale intracranial EEG data using multi-core machines and clusters

Haimonti Dutta, Huascar Fiorletta, Manoj Pooleery, Hatim Diab, Stanley German, David Waltz, Catherine A. Schevon
2011 Proceedings of the Third Workshop on Large Scale Data Mining Theory and Applications - LDMTA '11  
Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures that manifest in a variety of ways, including emotional or behavioral disturbances, convulsive movements, and loss of awareness. The problem of prediction of epileptic seizures is hard and most algorithms do not perform better than a random predictor [20] . An important reason why studies so far have been less than successful is that electroencephalogram (EEG) is not recorded at the granularity of the
more » ... zure generation process. Our collaborators at the Columbia University Medical School (CUMC) have been involved in a clinical trial which entails implanting a Micro-Electrode Array directly into the neocortex of epilepsy patients undergoing surgery to remove the portion of the brain from where seizures originate. The 96contact grid allows researchers to record at 30 KHz/channel which is a very high resolution data collection procedure compared to known state-of-the-art techniques and yields both local field and action potential data (.5 TB per patient per day). This large volume of data poses challenges for knowledge discovery and mining.
doi:10.1145/2002945.2002949 fatcat:2q4nua4m6jechhrkdwfe5cmuni

Data pre-processing for the preterm prediction study MFMU dataset

Ilia Vovsha, Ansaf Salleb-Aouissi, Axinia Radeva, Anita Raja, Hatim Diab, Ashish Tomar, Ashwath Rajan
Preterm birth is a major public health problem with profound implications on society. There would be extreme value in being able to identify women at risk of preterm birth during the course of their pregnancy. Previous research has largely focused on individual risk factors correlated with preterm birth (e.g. prior preterm birth, race, and infection) and less on combining these factors in a way to understand the complex etiologies of preterm birth. We attempt to address this gap by conducting a
more » ... deeper analysis of the preterm prediction study data collected by the NICHD Maternal Fetal Medicine Units (MFMU) Network, a high-quality data for over 3,000 singleton pregnancies having detailed study visits and biospecimen collection at 24, 26, 28 and 30 weeks gestation. Reports from this dataset used relatively straightforward biostatitistical methodologies such as relative risk assessments to measure associations between risk factors and PTB (Maternal Fetal Medicine Units Net- work. Biostatistical Coordinating Center NICHD Networks, 1995). These methods include descriptive statistics, Pearson correlation, Fisher's exact tests and linear/logistic regression where risk factors are studied independent of each other. In order to perform detailed experiments on this data using non-linear Support Vector Machines and other machine learning (ML) methodologies, it is necessary to complete several pre-processing steps that we describe in this report.
doi:10.7916/d8h139ct fatcat:oin7r7lkdzdnxboj6iop32wnqm

NILES 2020 Index

2020 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)  
Sarwat SS1: AI & Society Transformation 116 41 Hassanein Amer SA7: Testing & Verification 103 102 SA7: Testing & Verification 322 78 Hassnaa Yehia SA4: AI for Wireless Comm. 230 114 Hatim  ...  Afifi MO1: Artificial Intelligence 588 100 Mohamed Ashour SA4: AI for Wireless Comm. 315 21 Mohamed Azab SU7: Mechanical Systems 41 32 Mohamed Dessouky SA2: FPGA & ASIC 71 144 Mohamed Diab  ... 
doi:10.1109/niles50944.2020.9257943 fatcat:u37zk3xa3bfk5lflfo2zltlx5q

Negative Transfer: Arabic Language Interference to Learning English

Sabah Salman Sabbah
2016 Social Science Research Network  
(Abi Samara, 2000; Diab, 2003; Ali, 2006; Shabeer and Bughio, n.d.) . 4.  ...  There are three types of errors in the use of articles by the Arabicspeaking learners of English (Diab, 1996) . 1.  ... 
doi:10.2139/ssrn.2844015 fatcat:mgub4k72b5bbjplxhgqksh54fe

Arab Ethno-pop as Seen Through the Prism of the Jordanian Youth: Recreation of Locality, Scattering Globalization, and the Triumph of Amusement

2020 Journal of Education and Practice  
(Omr Diab Taaally maak, [Come with me]).  ...  this compositional import is obvious, and can be described as introducing simple chord progressions, supporting easy recalling melody, while native oriental sound shifting to foreign, diatonic sound (Hatim  ... 
doi:10.7176/jep/11-23-04 fatcat:boav4omclzcbpihtii4si4xyki

The Satisfaction of Students about how Instructional Design Quality Criteria for E-course in Distance Learning

Hatim Ibrahim
2020 Zenodo  
(Hassan Diab, 2006 ) developing a list of criteria for production and employment of computer multimedia software and its impact on academic achievement in middle schools, (Asmawi & Abdul Razak, 2006)  ...  researcher access to literature and Arabic and foreign research and studies related to the study, which targeted the electronic learning resources, including calendar: (; Hassan elbatta, 2008 , Hassan Diab  ... 
doi:10.5281/zenodo.4281104 fatcat:yyqvysd4hng7poleg54tzmrb4q

Dual Identities / Masking

Stephan Guth
2021 Journal of Arabic and Islamic studies  
By Muḥammad Diyāb (Mohamed Diab). Egypt, Germany, France 2016.  ...  In Mawlānā (“Our Master” / “The Preacher”), the unorthodox, free-minded imam Ḥātim is approached by a rich and influential contractor who is close to the inner circle around the President: his wife’s brother  ... 
doi:10.5617/jais.9499 fatcat:rqoje6oinzhsvezxtd7h753wli

Frame Semantic Tree Kernels for Social Network Extraction from Text

Apoorv Agarwal, Sriramkumar Balasubramanian, Anup Kotalwar, Jiehan Zheng, Owen Rambow
2014 Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics  
Acknowledgments We would like to thank CCLS's IT heads, Hatim Diab and Manoj Pooleery, for providing the infrastructure support.  ... 
doi:10.3115/v1/e14-1023 dblp:conf/eacl/AgarwalBKZR14 fatcat:uzqihlpexjb2dniuvlq2b5wmhm

THEMED SECTION (a-k, complete): Arrays of Egyptian and Tunisian Everyday Worlds: An Update on the project "In 2016—How it felt to live in the Arab World five years after the 'Arab Spring'"

Stephan Guth (ed.), Elena Chiti (ed.), Albrecht Hofheinz (ed.)
2018 Journal of Arabic and Islamic studies  
The TV show Anā Maṣrī ("I am Egyptian"), on ᵴtate-owned Nile TV channel, depicts Diab as follows: "Mohamed Diab is a young man who graduated from a faculty of commerce and worked for foreign banks and,  ...  In Mawlānā ("Our Master" / "The Preacher"), the unorthodox, freeminded imam Ḥātim is approached by a rich and influential contractor who is close to the inner circle around the President: his wife's brother  ... 
doi:10.5617/jais.6130 fatcat:bm5x3sx5vfh75gz3sdt3omsmfq

Dimension Reduction for Short Text Similarity and its Applications

Weiwei Guo
To CCLS staff members, Daniel Alicea, Hatim Diab, Kathy Hickey, Idrija Ibrahimagic, Derrick Lim, Axinia Radeva, who makes it a big family to me.  ...  LINKING TWEETS TO NEWS 100 [Guo and Diab, 2012b] .  ... 
doi:10.7916/d80z72c3 fatcat:vlggyytr55eofbd7xztmhifgoi

Leveraging Subjective Human Annotation for Clustering Historic Newspaper Articles [article]

Haimonti Dutta, William Chan, Deepak Shankargouda, Manoj Pooleery, Axinia Radeva, Kyle Rego, Boyi Xie, Rebecca Passonneau, Austin Lee and Barbara Taranto
2012 arXiv   pre-print
Dragomir Radev for his generous and insightful comments on drafts of the paper, Sam Lee and Hatim Diab for help with infrastructure and system development.  ... 
arXiv:1208.3530v1 fatcat:zyrcsngcgngrlnwzehzdiqdj24

A process for predicting manhole events in Manhattan

Cynthia Rudin, Rebecca J. Passonneau, Axinia Radeva, Haimonti Dutta, Steve Ierome, Delfina Isaac
2010 Machine Learning  
We would like to thank the following members of the Columbia CCLS: Roger Anderson, Dave Waltz, Nandini Bhardwaj, Diego Fulgueira, Ashish Tomar, Zhi An Liu, Nancy Burroughs-Evans, Daniel Alicea, Hatim Diab  ... 
doi:10.1007/s10994-009-5166-y fatcat:fyvpz7v5j5esddcqm2bzwsj6iq

The Comparative Effects of Self-Assessment and Peer Feedback on Improving Translation Quality

Mohammad Beiranvand, Ghafour Rezaie Golandouz
2017 Journal of Language and Translation   unpublished
The use of peer feedback by many researchers (Clark, 2003; Diab, 2011) has provided support for its positive in improving learner performance.  ...  Author's Email: such as Baker (1992) and Hatim and Mason (1997) show that those adopting these approaches make a comparison between source texts (STs) and target texts  ... 
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