A Survey on Prediction of Suicidal Ideation Using Machine and Ensemble Learning. - Akshma Chadha; Baijnath Kaushik (Comput. J., 2021)

Performance Evaluation of Learning Models for Identification of Suicidal Thoughts. - Akshma Chadha; Baijnath Kaushik (Comput. J., 2022)

A Hybrid Deep Learning Model Using Grid Search and Cross-Validation for Effective Classification and Prediction of Suicidal Ideation from Social Network Data. - Akshma Chadha; Baijnath Kaushik (New Gener. Comput., 2022)

Machine Learning Model for Sentiment Analysis on Mental Health Issues. - Baijnath Kaushik; Akshita Sharma; Akshma Chadha; Reya Sharma (ICCAE, 2023)

Comparative evaluation of deep dense sequential and deep dense transfer learning models for suicidal emotion prediction. - Akshita Sharma; Baijnath Kaushik; Akshma Chadha; Reya Sharma (Concurr. Comput. Pract. Exp., 2023)

Performance Evaluation of Learning Models for the Prognosis of COVID-19. - Baijnath Kaushik; Akshma Chadha; Reya Sharma (New Gener. Comput., 2023)

Performance evaluation of learning models for intrusion detection system using feature selection. - Baijnath Kaushik; Reya Sharma; Kulwant Dhama; Akshma Chadha; Surbhi Sharma (J. Comput. Virol. Hacking Tech., 2023)

A three layer stacked multimodel transfer learning approach for deep feature extraction from Chest Radiographic images for the classification of COVID-19. - Baijnath Kaushik; Akshma Chadha; Abhigya Mahajan; Malvika Ashok (Eng. Appl. Artif. Intell., 2025)