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Email Address
anandulle@sjce.ac.in
Education Qualification (All qualification including diploma)

M.Tech (Information Technology)

BE(Electronics and communication)

Research and Development

Medical Image Analysis

Journals Published

1. Anand ulle, T N Nagabhushan, Nandini monoli, “Segmentation and classification of nuclei based on extracting domianat shape features from histopathological images,”
article submitted to Journal of medical imaging (JMI), 2018
2. Anand ulle, T N Nagabhushan, Nandini monoli, “classification of histopathological images based on improved clump splitting.,” International journal of computer
application, (IJCA), 2018
3. Anand ulle, T N Nagabhushan, Nandini monoli, “An automated approach towards detection of Mitosis in Histopathological Images.,” International journal of computer
application, (IJCA), 2018
4. Manoli S. N, Ulle A. R, Nandini N. M, Rekha T. S. Classification of Breast Lesions using Modified Masood Score and Neural Network. Biomed Pharmacol J 2018;11(3).

Conferences Presented

1. Anand ulle, T N Nagabhushan, Nandini monoli, “clump splitting in histopathological images based on concave points.,” IEEE, International conference on cognitive
computing and information processing, (CCIP), 2015
2. Anand ulle, T N Nagabhushan, Nandini monoli, “An integrated convex hull and curvature based method for identifying valid comcave points.,” IEEE, International conference
on cognitive computing and information processing, (CCIP), 2016

Research and Development projects Awarded

1 Prediction of surgical site infection using sparse laboratory data. This projects aims at analyzing huge amount of blood sample test from patients who underwent gastro surgery. The proposed model was able to predict the patients susceptible for SSI better than other models proposed.
2. IOT - Designed a prototype for estimating the nutrients present in the soil
3. IOT - Design and Development of Smart Robot using ODROID SOC
3. Data Analytics - Designed a model for understanding the re-admission criteria for diabetic patients

Training Programs attended
20
Training Programs conducted and coordinated
2
Awards

1. Won the first place in modelling “Surgical site infection using sparse laboratory data”, 3rd Workshop on Data Mining for Medical Informatics: Learning Health, held at Chicago, 2016

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Research Interests

Computational Intelligence