Kumawat, H., Sharan, A., & Verma, S. (2025). Impact Analysis of Text Representation on Biomedical Multi-Label Text Classification with Deep Learning. Procedia Computer Science, 258, 3294-3304. https://doi.org/10.1016/j.procs.2025.04.587 

Verma, S., Kumawat, H., Sharan, A., Hooda, S., & Verma, N. (2025). Unveiling Biomedical Insights: A Semantic Pipeline from Document Entities to Knowledge Graph Analysis of Hallmarks of Cancer. Procedia Computer Science, 258, 2200-2209. https://doi.org/10.1016/j.procs.2025.04.470 

Verma, S., Kumar, A. & Sharan, A. WRGAT-PTBERT: weighted relational graph attention network over post-trained BERT for aspect based sentiment analysis. Appl Intell 55, 181 (2025). https://doi.org/10.1007/s10489-024-06011-x 

Rani, A., Kumawat, H., & Sharan, A. (2024, July). Patient-Centric Drug Recommendation from EHR Data: A Graph Neural Network-Based Approach. In International Conference on Data Science and Applications (pp. 153-166). Singapore: Springer Nature Singapore. https://link.springer.com/chapter/10.1007/978-981-96-2647-2_10 

Verma, S., Sharan, A. & Malik, N. Efficient Classification of Hallmark of Cancer Using Embedding-Based Support Vector Machine for Multilabel Text. New Generation Computing (2024). https://doi.org/10.1007/s00354-024-00248-3 

Verma, S., & Sharan, A. (2024). Unveiling the Biomarkers: Identifying Key Signatures for Cancer Hallmarks. EAI Endorsed Transactions on Pervasive Health and Technology. DOI: https://doi.org/10.4108/eetpht.10.5649 

Mehrotra, S., Sharan, A. & Varish, N. Improving search result clustering using nature inspired approach. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-023-18067-x    [Click here to get pdf]

Verma, S., & Sharan, A. (2023). Unveiling the Biomarkers: Identifying Key Signatures for Cancer Hallmarks. Presented at International Conference on Machine Learning And Applied Data Analytics December 15-16, 2023, Dehradun, India.

Dev, S., & Sharan, A. (2023). Annotated and Normalized Causal Relation Extraction Corpus for Improving Health Informatics. Presented at ICON 2023, 20th International Conference on Natural Language Processing, December 14-17, 2023.

Soni, G., Verma, S., Sharan, A., Ahmad, O. (2023). BioBERT-Based Model for COVID-Related Named Entity Recognition. In: Mishra, A., Gupta, D., Chetty, G. (eds) Advances in IoT and Security with Computational Intelligence. ICAISA 2023. Lecture Notes in Networks and Systems, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-99-5085-0_32 

Verma, S., Kumar, A. & Sharan, A. IAN-BERT: Combining Post-trained BERT with Interactive Attention Network for Aspect-Based Sentiment Analysis. SN COMPUT. SCI. 4, 756 (2023). [Click here to request pdf ] https://doi.org/10.1007/s42979-023-02229-7 

Verma, S., Kumar, A., & Sharan, A. (2023). MuCon: Multi-channel convolution for targeted sentiment classification. Multimedia Tools and Applications, 1-19. [Click here to request pdf. ] doi.org/10.1007/s11042-023-16586-1 

Verma, S., & Sharan, A. (2023). Incorporating semantics for text classification in biomedical domain. In Lecture Notes in Electrical Engineering (pp. 185–197). Springer Nature Singapore. https://dx.doi.org/10.1007/978-981-19-9090-8_17

Dev, S., & Sharan, A. (2023). Automatic construction of named entity corpus for adverse drug reaction prediction. In Advances in Intelligent Systems and Computing (pp. 245–255). Springer Nature Singapore. https://dx.doi.org/10.1007/978-981-99-0550-8_20

Ahmad O., Verma S., Azim S., Sharan A. (2022) Hybridizing Sentence Transformer Model with Multi-KNN for Biomedical Documents. In: Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-6460-1_11. 

Kumar, S., Sahu, A., & Sharan, A. (2022). Deep learning based architecture for entity extraction from covid related documents. In Information Systems and Management Science (pp. 419–427). Springer International Publishing. http://dx.doi.org/10.1007/978-3-031-13150-9_33

Azim, S., Dev, S., Kumar, S., & Sharan, A. (2022). Artificial Intelligence for Biomedical Informatics. In Artificial Intelligence Technologies for Computational Biology. CRC Press. https://www.taylorfrancis.com/chapters/edit/10.1201/9781003246688-6/artificial-intelligence-biomedical-informatics-shahid-azim-samridhi-dev-sushil-kumar-aditi-sharan

Kumar, A., Verma, S., & Sharan, A. (2020). ATE-SPD: Simultaneous extraction of aspect-term and aspect sentiment polarity using Bi-LSTM-CRF neural network. Journal of Experimental & Theoretical Artificial Intelligence, 33(3), 487–508. https://doi.org/10.1080/0952813x.2020.1764632

Kumar, A., Saini, M., & Sharan, A. (2020). Aspect category detection using statistical and semantic association. Computational Intelligence, 36(3), 1161–1182. https://doi.org/10.1111/coin.12327

Singh, A., & Sharan, A. (2018). Genetic-Fuzzy programming based linkage rule miner (gfplr-miner) for entity linking in semantic web. International Journal on Semantic Web and Information Systems, 14(3), 134–166. https://doi.org/10.4018/ijswis.2018070107

Mehrotra, S., Kohli, S., & Sharan, A. (2018). To identify the usage of clustering techniques for improving search result of a website. International Journal of Data Mining, Modelling and Management, 10(3), 229. https://doi.org/10.1504/ijdmmm.2018.093879 

Verma, S., Saini, M., & Sharan, A. (2017, August). Deep sequential model for review rating prediction. In 2017 Tenth International Conference on Contemporary Computing (IC3) (pp. 1-6). IEEE. [Click here to request pdf. ] 10.1109/IC3.2017.8284318 

Singh, J., & Sharan, A. (2016). A new fuzzy logic-based query expansion model for efficient information retrieval using relevance feedback approach. Neural Computing and Applications, 28(9), 2557–2580. https://doi.org/10.1007/s00521-016-2207-x

Verma, H., Agrawal, R. K., & Sharan, A. (2016). An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation. Applied Soft Computing, 46, 543–557. https://doi.org/10.1016/j.asoc.2015.12.022

Singh, J., & Sharan, A. (2016). Relevance Feedback-based Query Expansion Model using Ranks Combining and Word2Vec Approach. IETE Journal of Research, 62(5), 591–604. https://doi.org/10.1080/03772063.2015.1136575

Malik, N., & Sharan, A. (2016). Semantic Web Oriented framework for Knowledge Management in Agriculture Domain. International Journal of Web Applications., 8(3), 71-79. https://www.dline.info/ijwa/fulltext/v8n3/ijwav8n3_1.pdf

Singh, J., & Sharan, A. (2015). Relevance feedback based query expansion model using borda count and semantic similarity approach. Computational Intelligence and Neuroscience, 2015, 1–13. https://doi.org/10.1155/2015/568197