Publications

Kong, X., Gong, S., Su, L., Howard, N., Kong, Y. (2018). Detection of Acromegaly from Facial Photographs Using Machine Learning Methods, EBioMedicine, doi: 10.1016/j.ebiom.2017.12.015

Howard, N,. & Hussain, A. (2018). The Fundamental Code Unit of the Brain: Towards a New Model for Cognitive Geometry. Cognitive Computation. doi: 10.1007/s12559-017-9538-5.

Wang, Y., Howard, N., Kacprzyk, J., Frieder, O., Sheu, P., Fiorini, R. A., … & Widrow, B. (2018). Cognitive Informatics: Towards Cognitive Machine Learning and Autonomous Knowledge Manipulation. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 12(1), 1-13.

Ali, L., Khelil, K., Wajid, SK., Hussain, ZU., Shah, MA., Howard, A., Adeel, A., Shah, AA., Sudhakar, U., Howard, N., Hussain, A. (2017). Machine Learning Based Computer-aided Diagnosis of Liver Tumors. in 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)2017. pp. 139-145.

Shiva, AS., Gogate, M., Howard, N., Graham, B., Hussain, A. (2017). Complex-valued Computational Model of Hippocampal CA3 Recurrent Collaterals. in 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)2017. pp. 161-166

Dashtipour, K., Gogate, M., Adeel, A., Algarafi, A., Howard, N., Hussain, A. (2017). Persian Named Entity Recognition. 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 79-83.

Wang, Y., Valipour, M., Zatarain, OD., Gavrilova, ML., Hussain, A., Howard, N., Patel, S. (2017). Formal Ontology Generation by deep machine learning. in 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). pp. 6-15.

Bergmann, J. H. M., et al. (2017). “A Bayesian Assessment of Real-World Behavior During Multitasking.” Cognitive Computation, 9:749.

Elgendi, M., Howard, N., Lovell, N., Cichocki, A., Bearley, M., Abbott, D., Adatia, I. (2016). A Six-Step Framework on Biomedical Signal Analysis for Tackling Noncommunicable Diseases: Current and Future Perspectives. JMIR Biomedical Engineering, 1(1):e1. DOI: 10.2196/biomedeng.6401

Malik, Z. K., Hussain, Z. U., Kobti, Z., Lees, C. W., Howard, N., & Hussain, A. (2016). A New Recurrent Neural Network Based Predictive Model for Faecal Calprotectin Analysis: A Retrospective Study. arXiv preprint arXiv:1612.05794.

Amin, A., Anwar, S., Adnan, A., Nawaz, M., Howard, N., Qadir, J., et al. (2016). Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study. IEEE Access, 4, 7940-7957.

Poria, S., Cambria, E., Hussain, A., Howard, N. (2016) Fusing Audio, Visual, and Textual Clues for Sentiment Analysis from Multimodal Content. Neurocomputing, Vol 174: 50-59. DOI: 10.1016/ j.neucom.2015.01.095.

Wang, Y., Rolls, E. T., Howard, N., Raskin, V., Kinsner, W., Murtagh, F., et al. (2015). Cognitive Informatics and Computational Intelligence: From Information Revolution to Intelligence Revolution. International Journal of Software Science and Computational Intelligence (IJSSCI), 7(2), 50-69.

Cambria, E. Howard, N., Hussain, A. (2015). Multiple Kernal Learning for Multimodal Emotion and Sentiment Analysis, Extreme Learning Machines 2015, Hangzhou, China, December 15-17, 2015.

Jehel, L., Howard, N. (2015) Proactive Screening for Suicide Prevention. International Summit on Suicide Research, October 11-14, 2015, New York, NY.

Poria, S., Agarwal, Basant., Gelbukh, A., Hussain, A., Howard, N. (2014) Dependency-Based Semantic Parsing for Concept-Level Text Analysis. Computational Linguistics and Intelligent Text Processing. Lecture Notes in Computer Science, 8403, 113-127.

Hussain, A., Cambria, E., Schuller, B., Howard, N. (2014). Affective Neural Networks and Cognitive Learning Systems for Big Data Analysis, Neural Networks, Special Issue, 58, 1-3.

Cambria, E., Howard, N., Song, Y. & Wang, H. (2014). Semantic Multidimensional Scaling for Open Domain Sentiment Analysis. IEEE Intelligent Systems, 29 March/April.

Nave, O., Neuman, Y., Perlovsky, L. & Howard, N. (2014). How Much Information Should We Drop to Become Intelligent? Applied Mathematics and Computation, 245: 261-264.

Bergmann, J., Langdon, P., Mayagoita, R. & Howard, N. (2014). Exploring the Use of Sensors to Measure Behavioral Interactions: An Experimental Evaluation of Using Hand Trajectories. PLoS ONE, 9, e88080.

Dunn, J., Heredia, J. B. D., Burke, M., Gandy, L., Kanareykin, S., Kapah, O., Taylor, M., Hines, D., Freieder, O., Grossman, D., Howard, N., Koppel, M., Morris, S., Ortony, A. & Argamon, S. (2014). Language-Independent Ensemble Approaches to Metaphor Identification. CGAHI 2014: AAAI Workshop on Cognitive Computing for Augmented Human Intelligence. Quebec, Canada.

Howard, N., Jehel, L. & Arnal, R. (2014). Towards a Differential Diagnostic of PTSD Using Cognitive Computing Methods. International Conference on Cognitive Informatics and Cognitive Computing ICCI CC. London, UK: IEEE.

Poria, S., Gelbukh, A., Hussain, A., Bandyopadhyay, S. & Howard, N. (2013). Music Genre Classification: A Semi-supervised Approach. Pattern Recognition. Springer Berlin Heidelberg.

Poria, S., Gelbukh, A., Agarwal, B., Cambria, E. & Howard, N. (2013). Common Sense Knowledge Based Personality Recognition from Text. Advances in Soft Computing and Its Applications, Lecture Notes in Computer Science, Springer, 8266:2013, 484-496.

Howard, N. (2013). The Case for Intention Awareness in Security Systems. In Press, Journal of Cyber-Security and Digital Forensics, 1(1), in press.

Howard, N., Cambria, E. (2013). Development of a Diplomatic, Information, Military, Health, and Economic Effects Modeling System. International Journal of Privacy and Health Information Management 1:1, pp. 1-1.

Last, M., Assaf, D., Neuman, Y., Cohen, Y., Argamon, S., Howard, N., Frieder, O., & Koppel, M. (2013) Towards Metaphor Analysis for Natural Language Understanding. The 35th Annual Conference on Information Retrieval, March 24-27, 2013, Moscow, Russia.

Cambria, E., Mazzocco, T., Hussain, A., & Howard, N. (2013). Sentic Neurons: A Biologically Inspired Cognitive Architecture for Affective Common Sense Reasoning. In Procedia Computer Science, 00, 1­6.

Neuman, Y., Assaf, D., Cohen, Y., Last, M., Argamon, S., Howard, N. & Frieder, O. (2013). Metaphor Identification in Large Texts Corpora. PLoS One, 8.

Assaf, D., Howard, N., Neuman, Y., Last, M., Cohen, Y., Frieder, O., Argamon, & S., Koppel. (2013) Identifying-Noun Metaphors. 2013 IEEE Symposium Series on Computational Intelligence April 15-19, 2013, Singapore.

Howard, N., Bergmann, J., & Stein, J. (2013). Combined Modality of the Brain Code Approach for Early Detection and the Long-term Monitoring of Neurodegenerative Processes. Frontiers Special Issue INCF Course Imaging the Brain at Different Scales.

Bergmann, J., Graham, S., Howard, N., & McGregor, A. (2013). Comparison of Median Frequency Between Traditional and Functional Sensor Placements During Activity Monitoring. Measurement, 46, 2193-2200.

Howard, N., Stein, J., & Aziz, T. (2013). Early Detection of Parkinson’s Disease from Speech and Movement Recordings. Oxford Parkinson’s Disease Center Research Day 2013.

Howard, N., Bergmann, J., & Fahlstrom, R. (2013). Exploring the Relationship Between Everyday Speech and Motor Symptoms of Parkinson’s Disease as Prerequisite Analysis for Tool Development. Lecture Notes in Computer Science, MICAI, November 24-30, 2013, Mexico City, Mexico.

Howard, N. (2013). Approach Towards a Natural Language Analysis for Diagnosing Mood Disorders and Comorbid Conditions. Lecture Notes in Computer Science, MICAI, November 24-30, 2013, Mexico City, Mexico.

Howard, N. & Cambria, E. (2013). Intention awareness: improving upon situation awareness in human-centric environments. Human-centric Computing and Information Sciences, 3; 9, 1-17.

Howard, N. (2013). The Twin Hypotheses: Brain Code and the Fundamental Code Unit: Towards Understanding the Computational Primitive Elements of Cortical Computing. Lecture Notes in Artificial Intelligence, MICAI, November 24-30, 2013, Mexico City, Mexico.

Howard, N., Pollock, R., Prinold, J., Sinha, J., Newham, D., & Bergmann, J. (2013). Effect of Impairment on upper limb performance in an Ageing Population. The Human Computer Interaction International 2013 Conference (HCI) July 21-26, 2013, Las Vegas, Nevada.

Howard, N. (2013). Toward Understanding Analogical Mapping and Ideological Cataloguing in the Brain. Research Challenges in Information Science Series Conference (RCIS) May 29-31, 2013, Paris, France.

Last, M., Assaf, D., Neuman, Y., Cohen, Y., Argamon, S., Howard, N., Frieder, O., & Koppel, M. (2013) Towards Metaphor Analysis for Natural Language Understanding. The 35th Annual Conference on Information Retrieval, March 24-27, 2013, Moscow, Russia.

Assaf, D., Howard, N., Neuman, Y., Last, M., Cohen, Y., Frieder, O., Argamon, & S., Koppel (2013). Identifying -Noun Metaphors. 2013 IEEE Symposium Series on Computational Intelligence April 15-19, 2013, Singapore.

Bergmann, J., Howard, N. (2013). Design Considerations for a Wearable Sensor Network that Measures Accelerations during Water-Ski Jumping. IEEE Body Sensor Network Conference, May 6-­9, 2013, Cambridge, Massachusetts.

Howard, N., Rao, D., Fahlstrom, R., & Stein, J. (2013). The Fundamental Code Unit: A Framework for Biomarker Analysis. The 2nd Neurological Biomarkers Conference at the 2013 Biomarker Summit. San Francisco, California.

Assaf, D., Neuman, Y.; Cohen, Y.; Argamon, S.; Howard, N.; Last, M.; Koppel, M. (2013). Why “dark thoughts” aren’t really dark: A novel algorithm for metaphor identification. In 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), 60-65. IEEE.

Cambria, E., White, B., Durrani, T., & Howard, N. (2012). Computational Intelligence for Natural Language Processing. IEEE Computational Intelligence Magazine, 9(1), 19-63.

Bergmann, J., Graham, S., Howard, N., & McGregor, (2012). A. Comparison of median frequency between traditional and functional sensor placements during activity monitoring, Measurement, 46:7, 2193-2200.

Howard, N. & Bergmann, J. (2012). Combining Computational Neuroscience and Body Sensor Networks to Investigate Alzheimer’s Disease. Journal of Functional Neurology, Rehabilitation and Ergonomics, 2(1), 29-38

Bergmann, J. & Howard, N. (2012). Combining Computational Neuroscience and Body Sensor Networks to Investigate Alzheimer’s Disease. BMC Neuroscience, 13(supp), 178.

Howard, N. (2012) Brain Space: Relating Neuroscience to Knowledge About Everyday Life. Cognitive Computation, published online August 2012.

Howard, N. (2012). Brain Language: The Fundamental Code Unit. The Brain Sciences Journal, 1(1), 4-45.

Howard, N. (2012). Energy Paradox of the Brain. The Brain Sciences Journal, 1(1), 46-61.

Howard, N. & Lieberman, H. (2012). Brain Space: Automated Brain Understanding and Machine Constructed Analytics in Neuroscience. Brain Sciences Journal, 1(1), 85-97.

Howard, N. & Guidere, M. (2012). LXIO The Mood Detection Robopsych. The Brain Sciences Journal, 1(1), 98-109.

Howard, N. & Kanareykin, S. (2012). Transcranial Ultrasound Application Methods: Low-Frequency Ultrasound as a Treatment for Brain Dysfunction. The Brain Sciences Journal, 1(1), 110-124.

Howard, N. & Bergmann, J. (2012). Combining Computational Neuroscience and Body Sensor Networks to Investigate Alzheimer’s Disease. Organization for Computational Neurosciences, July 21-26, 2012, Atlanta/Decatur.

Howard, N. (2012). Intention Awareness in Human-Machine Interaction Sensemaking in Joint Cognitive Systems. International Conference on Information Sciences and Interaction Science, June 26-28, 2012, Jeju Island, Korea, 293-299.

Howard, N. (2017). Approach to Study the Brain: Towards the Early Detection of Neurodegenerative Disease, London, UK, Cambridge Scientific Publishing. ISBN 978-1-908106-49-0. In Print.

Howard, N. (2017). The Brain Language, London, UK, Cambridge Scientific Publishing. ISBN 978-1­908106-50-6. In Print.

Jehel, L., Arnal, R., Carmelo, D., Howard, N. (2015) Suicide Crisis in the Digital Age (chapter). Understanding Suicide – Risk, Assesment, Prevention, and Treatment, Editor Courtet, P. Springer.

Jehel, L., Arnal, R., Carmelo, D., Sigward, J.M., Howard, N. (2015) Les Troubles Dépressifs et la Crise Suicidaire (chapter). Therapie des Victimes, Editor Lopez, G. et al. Springer.

Howard, N. (2015). The Brain Language: Psychotrauma Spectrum Disorder and Cybernetic Detection of Disease Conditions and Comorbidities. Université de Paris Descartes.

Howard, N. (2014).Approach to Study the Brain: Towards the Early Detection of Neurodegenerative Disease, Oxford University, Bodleian Library.

Hussain, A., Cambria, E., Schuller, B. & Howard, N. (2014). Affective Neural Networks and Cognitive Learning Systems for Big Data Analysis. Neural Network, 58, 1-3.