collaborators

6 papers

cs.LG2026

Ontology-Based Knowledge Modeling and Uncertainty-Aware Outdoor Air Quality Assessment Using Weighted Interval Type-2 Fuzzy Logic

Md Inzmam, Ritesh Chandra, Sadhana Tiwari +2

Outdoor air pollution is a major concern for the environment and public health, especially in areas where urbanization is taking place rapidly. The Indian Air Quality Index (IND-AQ…

cs.DC2025

A Review of Ontology-Driven Big Data Analytics in Healthcare: Challenges, Tools, and Applications

Ritesh Chandra, Sonali Agarwal, Navjot Singh +1

Exponential growth in heterogeneous healthcare data arising from electronic health records (EHRs), medical imaging, wearable sensors, and biomedical research has accelerated the ad…

cs.DB2025

Real-Time Health Analytics Using Ontology-Driven Complex Event Processing and LLM Reasoning: A Tuberculosis Case Study

Ritesh Chandra, Sonali Agarwal, Navjot Singh

Timely detection of critical health conditions remains a major challenge in public health analytics, especially in Big Data environments characterized by high volume, rapid velocit…

cs.AI2025

A Diagnosis and Treatment of Liver Diseases: Integrating Batch Processing, Rule-Based Event Detection and Explainable Artificial Intelligence

Ritesh Chandra, Sadhana Tiwari, Satyam Rastogi +1

Liver diseases pose a significant global health burden, impacting many individuals and having substantial economic and social consequences. Rising liver problems are considered a f…

cs.LG2025

Innovative Framework for Early Estimation of Mental Disorder Scores to Enable Timely Interventions

Himanshi Singh, Sadhana Tiwari, Sonali Agarwal +3

Individual's general well-being is greatly impacted by mental health conditions including depression and Post-Traumatic Stress Disorder (PTSD), underscoring the importance of early…

cs.LG2025

Multimodal Data-Driven Classification of Mental Disorders: A Comprehensive Approach to Diagnosing Depression, Anxiety, and Schizophrenia

Himanshi Singh, Sadhana Tiwari, Sonali Agarwal +3

This study investigates the potential of multimodal data integration, which combines electroencephalogram (EEG) data with sociodemographic characteristics like age, sex, education,…