Amrutanshu Panigrahi

Robust feature selection for cancer microarray data using a hybrid mRMR and Binary Lion Optimization Algorithm

Bibhuprasad Sahu, Amrutanshu Panigrahi, Abhilash Pati, B. K. Madhavi et autres

Cancer microarray datasets often contain many irrelevant, duplicate, and even noisy features, which are likely to reduce the accuracy of classification algorithms. As a branch of feature engineering, the feature selection process aims to improve the classification performance of the desired microarray …

in, us, np (code pays fourni par la source)

Retraction Note: Enhancing blockchain transaction classification with ensemble learning approaches

Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Rourab Paul et autres

After publication, concerns were raised regarding the presence of nonstandard vocabulary, the incorrect definitions of key evaluation metrics, insufficient description of dataset use, and performance values that could not be reconciled with the information provided. The Editors requested explanations, the code underlying …

in (code pays fourni par la source)

Feature selection from Gene expression Microarray Alzheimer’s disease (AD) Datasets using Binary Election Optimizer with Deep mRMR

Bibhuprasad Sahu, Amrutanshu Panigrahi, Abhilash Pati, Manoranjan Dash et autres

in, us (code pays fourni par la source)

Deep Learning Meets Barber Optimization: Toward Smarter Wheat Disease Detection

Bibhuprasad Sahu, Ravinder Singh Rathore, Amrutanshu Panigrahi, Abhilash Pati et autres

in, us (code pays fourni par la source)

SMOTETomek Enriched GWO: A Hybrid Approach for Diabetes Disease Prediction

Peddapally Ridhi Sai, Rajidi Reddy Likitha, Bibhuprasad Sahu, Amrutanshu Panigrahi et autres

This paper presents a hybrid machine learning framework for binary classification that combines resampling, ensemble learning, and sophisticated feature engineering. Combining SMOTETomek resampling with Grey Wolf Optimization (GWO), such as interactionand ratio-based features, successfully addresses class imbalance and improves predictive accuracy. Through …

An Ensembled Hybrid Machine Learning Approach (EHMLA) for Enhanced Disease Diagnosis

Sambit Ranjan Pattanayak, Umang Kumar Agrawal, Abhilash Pati, Amrutanshu Panigrahi et autres

Prognosing the earliest manifestation of various diseases, including Breast cancer, Lung cancer, Chronic Kidney Disease, and Cervical cancer, etc., is a requirement for well-timed diagnosis, therapy, and medication, as this situation is a substantial cause of demise worldwide. Machine Learning (ML), due …

in, us (code pays fourni par la source)

Explainable deep learning for skin cancer detection using swish-activated convolutional networks

Subhayan Mukherjee, Khushbu Chandrakar, Subrata Chowdhury, Vijayalakshmi Senniappan et autres

Skin cancer is among the most frequent and fatal illnesses in the world, but early and correct diagnosis is one of the main challenges because of the complicated visual patterns of skin lesions and the absence of interpretable diagnostic devices. Conventional techniques …

in, np, Éthiopie (code pays fourni par la source)

Predicting Financial Distress and Financial Viability of Selected State Cooperative Banks

Smruti Ranjan Sahoo, Prafulla Kumar Swain, Dash Manoranjan, Preeti Y Shadangi et autres

in (code pays fourni par la source)

Weighted Rank Difference Ensemble Binary Cat Mouse Optimization for Feature Selection

Bibhuprasad Sahu, Abhaya Kumar Panda, Tuhina Panda, Ashis Pati et autres

in (code pays fourni par la source)

TrustRank-PKI: A Blockchain-Based PKI Using Adaptive Trust-Aware Consensus for Identity and Certificate Management

Amrutanshu Panigrahi, Amaresh Parida, Abhilash Pati, Bibhuprasad Sahu et autres

in, ae, us (code pays fourni par la source)

Blockchain for Secure and Equitable Health Data Management

Ravindra Pandey, Arun Khatri, Amrutanshu Panigrahi, H. Malathi et autres

Blockchain technologies have a decentralized and secure approach toward managing sensitive healthcare data to enhance interoperability among healthcare providers while ensuring improved privacy. It provides, in practice, patient-controlled data access so that data integrity can be ensured. It can change how healthcare …

us, in (code pays fourni par la source)

Privacy‐Preserving and Scalable Authentication Using zk‐SNARK‐Based ZKP Blockchain PKI

Amrutanshu Panigrahi, Bibhuprasad Sahu, Abhilash Pati, S. Chowdhury

Public key infrastructure (PKI) establishes secure communication over digital interfaces and authorized access to technology resources. Traditional PKI systems have weaknesses such as key compromise, trust management failure, escalated vulnerabilities due to a unitary point of failure, and other shortcomings, unlike basic …

in (code pays fourni par la source)