As most of you are aware deep learning is invading almost all arenas of science and technology. Out of them, healthcare happens to be the foremost. Recent developments in the field of healthcare utilizing the tools and techniques from deep learning formalism is creating a paradigm shift. Global giants such as Google and Microsoft are investing heavily in this direction.

Apart from the possibility of high quality publications, the research in this area will also open up excellent job opportunities for undergraduate and graduate students in various streams of engineering and sciences.

Yet another are where the efficacy of deep learning is beginning to get revealed is financial engineering. Compared to the classical methods used in financial engineering, tools of deep learning are extremely efficient to analyse and predict market dynamics. The research in market economy using the techniques of deep learning will result in patentable algorithms and also in start-ups with high potential for success.

The systems such as financial markets and human body which act as the source of data consist of many interacting subsystems. The traditional reductionist approach of analysing the individual subsystems is insufficient. A novel branch of physics termed Complex system theory is essential for the analysis of such large spatio-temporal data.

One of the most important open problems that grabs the attention of data scientists is the integration of measures derived from complex system theory with deep learning techniques. It will be highly revealing to view the deep learning formalism from a complex system perspective and also to effectively employ the complex measures as learning features for a deep learning network.

Considering the immediate need and the infinite potential of exploring the data from healthcare and financial sectors, Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Amrita Vishwa Vidyapeetham Coimbatore has decided to conduct a one day work shop on "Deep learning for complex systems with special focus on healthcare & finance".

1. Malaria image dataset
2. Tuberculosis image dataset
3. Intestinal parasites image dataset

Venue: CEN, Amrita School of Engineering Coimbatore, Amrita Vishwa Vidyapeetham

Date: 11/11/2017

Time: 09.00 am to 06.00 pm (please find below the detailed schedule)

09.00 -10.00 - "The inexplicable efficacy of deep learning" - Prof. K. P. Soman (Professor & Head, CEN) PPT

10:00 -10:30 - "How to analyse data from complex systems" - Dr. Gopalakrishnan E. A. (Assistant Professor, CEN)

10:30 - 10:45 - Tea break

10:45 - 11.15 - "Deep learning for medical image processing" - Mrs. Sowmya V. (Assistant Professor, CEN) PPT

11:15 - 11:45 - "Different deep learning architectures for stock price prediction" - Neethu Mohan and Premjith B (PhD Scholar, CEN)

11:45 - 12:15 - "Deep learning to detect sleep apnea: A case study"

12:15 - 12:45 - "Deep learning for ECG analysis"

12:45 - 14:00 - Lunch

14:00 - 15:30 - "Deep learning hands-on" - Mr. Vinaykumar R (PhD Scholar, CEN)

15:30 - 16:00 - Tea break

16:00 - 16:30 - "Developing new low-cost devices for Bio-medical Signal Acquistion" by Mr. K. Guruvayurappan and Mr. Sajith Variyar V. V.

16:30 - 17:00 - "Road ahead: Possible collaborative projects & papers" - Panel discussion

17:00 - 18:00 - Concluding remarks and feedback from participants


Registration

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Books published from CEN on Signal processing and Machine learning

1. Dr. K.P. Soman, Prabaharan Poornachandran, Sachin Kumar S and Neethu Mohan, "Convex Optimization based Signal Processing for IOT." [Upcoming Book]


2. Dr. K.P. Soman and Dr. Ramachandran K.I, "Insight into Wavelets From Theory to Practice.", Prentice-Hall India 2004.


3. Dr. K.P. Soman, Shyam Diwakar, Ajay V., "Insight into Data Mining From Theory to Practice.", Prentice-Hall India, 2006.


4. Dr. K.P. Soman, Ajay. V, Loganathan R., "Machine Learning with SVM and other Kernel Methods.",Prentice-Hall India, 2009.


5. Dr. K.P.Soman, and Ramanthan, "Digital signal and Image Processing-The Sparse Way." Elsevier Publications, 2012.


6. Dr. Deepa G., Dr. Krishnan Namboodiri, "Bioinformatics: Sequential and Structural Analysis.", Narosa Publications.


7. Dr. K.I Ramachandran., Dr. Deepa, Dr. Krishnan Namboori, "Computational Chemistry and Molecular Modelling." -Springer international.


8. "Fractals for Everyone." Online version: http://cen.amritafoss.org/downloads/ (link is external) Manu Unni, Praveen Krishnan, Dr. K. P. Soman.

Publication from CEN in the area of Finance & healthcare data analysis using deep learning

• Pathinarupothi. R. K, Vinaykumar. R, Rangan. E, Gopalakrishnan. E.A and Soman. K. P, "Instantaneous heart rate as a robust feature for sleep apnea severity detection using deep learning" - IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017, pp. 293-296.[paper]


• Pathinarupothi. R. K, Vinaykumar. R, Rangan. E, Gopalakrishnan. E.A and Soman. K. P, "Single Sensor Techniques for Sleep Apnea Diagnosis Using Deep Learning" - IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017, pp. 524-529. [paper]


• Sujadevi. V. G, Soman. K. P, Sachin Kumar. S, Neethu Mohan, "A novel cyclic convolution based regularization method for power-line interference removal in ECG signal"- Springer AISC series proceedings of third International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS 2017, pp.116-126.[paper]


• Sujadevi. V. G, Soman. K. P, Vinaykumar. R, "Real-Time Detection of Atrial Fibrillation from Short Time Single Lead ECG Traces Using Recurrent Neural Networks"- Springer AISC series proceedings of the International Symposium on Intelligent Systems Technologies and Applications 2017.[paper]


• Sujadevi. V. G, Soman. K. P, Vinaykumar. R Prem Sankar, "Deep models for Phonocardiography (PCG) classification"- IEEE International Conference on Intelligent Communication and Computational Techniques (ICCT), 2017.[under print]


• Sujadevi. V. G, Soman. K. P, Vinaykumar. R Prem Sankar, "Anomaly detection in Phonocardiogram employing Deep learning"- Springer AISC series proceedings of 4th International Conference on Computational Intelligence in Data Mining (ICCIDM), 2017.[under print]


• Deepthi Praveenlal Kuttichira, Gopalakrishnan.E.A, Viajy Krishna Menon, Soman.K.P, "Stock Price Prediction Using Dynamic Mode Decomposition", Sixth IEEE International Conference on Advances in Computing, Communications and Informatics, ICACCI, 2017.[under print]


• Sreelekshmy .S, Vinaykumar. R, Gopalakrishnan.E.A, Viajy Krishna Menon, Soman.K.P, "Stock Price Prediction Using LSTM,RNN AND CNN-sliding window model", Sixth IEEE International Conference on Advances in Computing, Communications and Informatics, ICACCI, 2017.[under print]

Developed by Vinayakumar R and Harikrishnan N B