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Notable Journal publications

1. Becker, Jan U., David Mayerich, Meghana Padmanabhan, Jonathan Barratt, Angela Ernst, Peter Boor, Pietro A. Cicalese, Chandra Mohan, Hien V. Nguyen, and Badrinath Roysam. "Artificial intelligence and machine learning in nephropathology." Kidney International (2020).​

About: In this review, we discuss AI in nephropathology and explain how AI can enhance the reproducibility of nephropathology results for certain parameters in the context of precision medicine using advanced architectures, such as convolutional neural networks, that are currently the state of the art in machine learning software for this task.

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2. Padmanabhan, Meghana, Pengyu Yuan, Govind Chada, and Hien Van Nguyen. "Physician-friendly machine learning: A case study with cardiovascular disease risk prediction." Journal of clinical medicine 8, no. 7 (2019): 1050.

About: This experiment attempts the break the perception in the medical community about the accessibility of Machine Learning tools to highly trained experts by providing empirical evidence for the performance of AutoML in comparison to human expert on two cardiovascular disease risk prediction datasets.

3. Sahay, Gaurangi, P. Meghana, Vadali Venkata Sravani, T. Prabha Venkatesh, and Viswavardhan Karna. "SDR based single channel S-AIS receiver for satellites using system generator." In 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pp. 1-6. IEEE, 2016.

About: The Satellite-Automatic Identification System (S-AIS) is a critical maritime monitoring system that ensures safety and security of ships by sharing vital information regarding other ships as well as watercrafts in the vicinity. This paper covers the Software Defined Radio (SDR) based receiver designs at the satellite receivers, in order to reliably receive the transmitted AIS message from the ships.

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