Tripti Swarnkar

According to our database, Tripti Swarnkar authored at least 24 papers between 2012 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

PerSceptoMed 1.0: An advanced machine learning model for demographic-based antibiotic susceptibility prediction in Pseudomonas aeruginosa infections.

Sweta Padma Routray, Saswati Mahapatra, Debasish Swapnesh Kumar Nayak, Swayamprabha Sahoo, Bhabani Shankar Das, Enketeswara Subudhi, Rajashree Panigrahy, Tripti Swarnkar

Eng. Appl. Artif. Intell., 2025

ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer.

Debasish Swapnesh Kumar Nayak, Ruchika Das, Santanu Kumar Sahoo, Tripti Swarnkar

Comput. Biol. Chem., 2025

2024

DnnARs: An Artificial Intelligence Technique for Prediction of Antimicrobial Resistant Strains in E. coli Bacteria Causing Urine Tract Infection.

Debasish Swapnesh Kumar Nayak, Arpita Priyadarshini, Pabani Mahanta, Tejaswini Das, Santanu Kumar Sahoo, Tripti Swarnkar

SN Comput. Sci., December, 2024

Web-Based Tools Validation for Antimicrobial Resistance Prediction: An Empirical Comparative Analysis.

Sweta Padma Routray, Swayamprabha Sahoo, Debasish Swapnesh Kumar Nayak, Sejal Shah, Tripti Swarnkar

SN Comput. Sci., January, 2024

Efficient Gene Expression Data Analysis using ES-DBN For Microarray Cancer Data Classification.

Swati Sucharita, Barnali Sahu, Tripti Swarnkar

EAI Endorsed Trans. Pervasive Health Technol., 2024

Classification of cancer microarray data using a two-step feature selection framework with moth-flame optimization and extreme learning machine.

Swati Sucharita, Barnali Sahu, Tripti Swarnkar, Saroj K. Meher

Multim. Tools Appl., 2024

Weighted Bayesian Belief Network for diabetics: a predictive model.

Shweta Kharya, Sunita Soni, Abhilash Pati, Amrutanshu Panigrahi, Jayant P. Giri, Hong Qin, Saurav Mallik, Debasish Swapnesh Kumar Nayak, Tripti Swarnkar

Frontiers Artif. Intell., 2024

2022

Capsule network based analysis of histopathological images of oral squamous cell carcinoma.

Santisudha Panigrahi, Jayshankar Das, Tripti Swarnkar

J. King Saud Univ. Comput. Inf. Sci., 2022

2021

Deep filter bridge for malaria identification and classification in microscopic blood smear images.

Priyadarshini Adyasha Pattanaik, Tripti Swarnkar, Debabala Swain

Int. J. Adv. Intell. Paradigms, 2021

Prediction of Smoking Addiction Among Youths Using Elastic Net and KNN: A Machine Learning Approach.

Shreerudra Pratik, Debasish Swapnesh Kumar Nayak, Rajendra Prasath, Tripti Swarnkar

Proceedings of the Mining Intelligence and Knowledge Exploration, 2021

Integrative Analysis of miRNA-mRNA Expression Data to Identify miRNA-Targets for Oral Cancer.

Saswati Mahapatra, Rajendra Prasath, Tripti Swarnkar

Proceedings of the Mining Intelligence and Knowledge Exploration, 2021

2020

Elitism based Multi-Objective Differential Evolution for feature selection: A filter approach with an efficient redundancy measure.

Subrat Kumar Nayak, Pravat Kumar Rout, Alok Kumar Jagadev, Tripti Swarnkar

J. King Saud Univ. Comput. Inf. Sci., 2020

2019

Vision-based malaria parasite image analysis: a systematic review.

Priyadarshini Adyasha Pattanaik, Tripti Swarnkar

Int. J. Bioinform. Res. Appl., 2019

Fractal Geometry for Early Detection and Histopathological Analysis of Oral Cancer.

Santisudha Panigrahi, Juber Rahmen, Swagatika Panda, Tripti Swarnkar

Proceedings of the Mining Intelligence and Knowledge Exploration, 2019

Prediction of Depression Using EEG: A Comparative Study.

Namrata P. Mohanty, Sweta Shree Dash, Sandeep Sobhan, Tripti Swarnkar

Proceedings of the Progress in Advanced Computing and Intelligent Engineering, 2019

Automated Classification of Oral Cancer Histopathology images using Convolutional Neural Network.

Santisudha Panigrahi, Tripti Swarnkar

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018

Comparative Analysis of Morphological Techniques for Malaria Detection.

Priyadarshini Adyasha Pattanaik, Tripti Swarnkar

Int. J. Heal. Inf. Syst. Informatics, 2018

Elitism-based multi-objective differential evolution with extreme learning machine for feature selection: a novel searching technique.

Subrat Kumar Nayak, Pravat Kumar Rout, Alok Kumar Jagadev, Tripti Swarnkar

Connect. Sci., 2018

2017

Comparative Study of Computational Tools for Hub Gene Selection from Genetic Network using Microarray Data.

Bijeta Mandal, Saswati Mahapatra, Tripti Swarnkar

POLIBITS, 2017

A Higher Education Predictive Model Using Data Mining Techniques.

Subhalaxmi Panda, Priyadarshini Adyasha Pattanaik, Tripti Swarnkar

Proceedings of the Joint Proceedings of the 3rd Modelling Symposium (ModSym), 2017

Object detection technique for malaria parasite in thin blood smear images.

Priyadarshini Adyasha Pattanaik, Tripti Swarnkar, Debdoot Sheet

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2015

Identifying dense subgraphs in protein-protein interaction network for gene selection from microarray data.

Tripti Swarnkar, Sérgio Nery Simões, Anji Anurak, Helena Paula Brentani, Jyotirmoy Chatterjee, Ronaldo Fumio Hashimoto, David Correa Martins, Pabitra Mitra

Netw. Model. Anal. Health Informatics Bioinform., 2015

2014

Multiview Clustering on PPI Network for Gene Selection and Enrichment from Microarray Data.

Tripti Swarnkar, Sérgio Nery Simões, David Correa Martins, Anji Anurak, Helena Paula Brentani, Ronaldo Fumio Hashimoto, Pabitra Mitra

Proceedings of the 2014 IEEE International Conference on Bioinformatics and Bioengineering, 2014

2012

Graph based unsupervised feature selection for microarray data.

Tripti Swarnkar, Pabitra Mitra

Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2012