Artificial Intelligence Methods Based Hierarchical Classification of Frontotemporal Dementia to Improve Diagnostic Predictability. - Km Poonam; Rajlakshmi Guha; Partha Pratim Chakrabarti (CoRR, 2021)

Accurate Prediction of Alzheimer's Disease Progression Trajectory via a Novel Encoder-Decoder LSTM Architecture. - Km Poonam; Rajlakshmi Guha; Partha Pratim Chakrabarti (EMBC, 2023)

Frontotemporal Dementia Detection Model Based on Explainable Machine Learning Approach. - Km Poonam; Rajlakshmi Guha; Partha Pratim Chakrabarti (ICCIDS, 2023)

Explainable Decision Tree-Based Screening of Cognitive Impairment Leveraging Minimal Neuropsychological Tests. - Km Poonam; Aayush Prasad; Rajlakshmi Guha; Aritra Hazra; P. P. Chakrabarti 001 (PReMI, 2023)

Exploring Self-Supervised Models for Depressive Disorder Detection: A Study on Speech Corpora. - Bubai Maji; Shazia Nasreen; Rajlakshmi Guha; Aurobinda Routray; Debabrata Majumdar; Km Poonam (EMBC, 2024)

A Regression Framework for Predicting Cognitive Decline in Frontotemporal Dementia using Recurrent Neural Networks. - Km Poonam; Rajlakshmi Guha; Partha P. Chakrabarti (EMBC, 2024)

Artificial Intelligence Based Hierarchical Classification of Frontotemporal Dementia. - Km Poonam; Rajlakshmi Guha; Partha P. Chakrabarti (EMBC, 2024)

Hierarchical Classification of Frontotemporal Dementia Subtypes Utilizing Tabular-to-Image Data Conversion with Deep Learning Methods. - Km Poonam; Venkata Sathwik Kotra; Rajlakshmi Guha; Partha Pratim Chakraborty (ICPR (11), 2024)

Predicting Alzheimer's Disease Progression Using a Versatile Sequence-Length-Adaptive Encoder-Decoder LSTM Architecture. - Km Poonam; Rajlakshmi Guha; Partha Pratim Chakraborty (IEEE J. Biomed. Health Informatics, 2024)

Dual Bi-LSTM-GRU based stance detection in tweets ordered classes. - Km Poonam; Tene Ramakrishnudu (Neural Comput. Appl., 2025)