Towards predicting academic impact from mainstream news and weblogs: A heterogeneous graph based approach. - Mohan Timilsina; Brian Davis 001; Michael Taylor 002; Conor Hayes (ASONAM, 2016)

Predicting citations from mainstream news, weblogs and discussion forums. - Mohan Timilsina; Brian Davis 001; Michael Taylor 002; Conor Hayes (WI, 2017)

Social impact assessment of scientist from mainstream news and weblogs. - Mohan Timilsina; Waqas Khawaja; Brian Davis 001; Michael Taylor 002; Conor Hayes (Soc. Netw. Anal. Min., 2017)

A 2-Layered Graph Based Diffusion Approach for Altmetric Analysis. - Mohan Timilsina; Haixuan Yang; Dietrich Rebholz-Schuhmann (ASONAM, 2018)

A Diffusion-Based Method for Entity Search. - Pablo Torres-Tramón; Mohan Timilsina; Conor Hayes (ICSC, 2019)

Predicting links between tumor samples and genes using 2-Layered graph based diffusion approach. - Mohan Timilsina; Haixuan Yang; Ratnesh Sahay; Dietrich Rebholz-Schuhmann (BMC Bioinform., 2019)

Role of patient descriptors in predicting antimicrobial resistance in urinary tract infections using a decision tree approach: A retrospective cohort study. - Meera Tandan; Mohan Timilsina; Martin Cormican; Akke Vellinga (Int. J. Medical Informatics, 2019)

Heat diffusion approach for scientific impact analysis in social media. - Mohan Timilsina; Mathieu d'Aquin; Haixuan Yang (Soc. Netw. Anal. Min., 2019)

On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. - Sameh K. Mohamed; Brian Walsh; Mohan Timilsina; Vít Novácek; Maria Torrente; Fabio Franco; Mariano Provencio; Adrianna Janik; Luca Costabello; Pontus Stenetorp; Pasquale Minervini (AMIA, 2021)

Semi-supervised regression using diffusion on graphs. - Mohan Timilsina; Alejandro Figueroa 001; Mathieu d'Aquin; Haixuan Yang (Appl. Soft Comput., 2021)

Discovering symptom patterns of COVID-19 patients using association rule mining. - Meera Tandan; Yogesh Acharya; Suresh Pokharel; Mohan Timilsina (Comput. Biol. Medicine, 2021)

Explainable Artificial Intelligence (XAI) to Enhance Trust Management in Intrusion Detection Systems Using Decision Tree Model. - Basim Mahbooba; Mohan Timilsina; Radhya Sahal; Martin Serrano (Complex., 2021)

What identifies different age cohorts in Yahoo! Answers? - Alejandro Figueroa 001; Mohan Timilsina (Knowl. Based Syst., 2021)

Integration of Clinical Information and Imputed Aneuploidy Scores to Enhance Relapse Prediction in Early Stage Lung Cancer Patients. - Mohan Timilsina; Samuele Bousi; Dirk Fey; Adrianna Janik; Maria Torrente; Mariano Provencio; Alberto Bermúdez; Enric Carcereny; Luca Costabello; Delvys Rodriguez Abreu; Manuel Cobo; Rafael Castro; et al. (AMIA, 2022)

Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients. - Adrianna Janik; Maria Torrente; Luca Costabello; Virginia Calvo; Brian Walsh; Carlos Camps; Sameh K. Mohamed; Ana L. Ortega; Vít Novácek; Bartomeu Massutí; Pasquale Minervini; M. Rosario Garcia Campelo; et al. (CoRR, 2022)

Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding. - Mohan Timilsina; Vít Novácek; Mathieu d'Aquin; Haixuan Yang (Neural Networks, 2022)

Synergy Between Embedding and Protein Functional Association Networks for Drug Label Prediction Using Harmonic Function. - Mohan Timilsina; Declan Patrick Mc Kernan; Haixuan Yang; Mathieu d'Aquin (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Foundation Data Space Models: Bridging the Artificial Intelligence and Data Ecosystems (Vision Paper). - Edward Curry; Tarek Zaarour; Yang Yang 008; Mohan Timilsina; Majjed Al-Qatf; Rafiqul Haque (IEEE Big Data, 2023)

Engineering Data Assets for Public Health Applications: A Covid-19 Case Study. - Michael Scriney; Mohan Timilsina; Edward Curry; Lukasz Porwol; Dongyun Nie; Darren Dahley; Jaime B. Fernandez; Mathieu d'Aquin; Mark Roantree (IEEE Big Data, 2023)

Knowledge Graphs, Clinical Trials, Dataspace, and AI: Uniting for Progressive Healthcare Innovation. - Mohan Timilsina; Saeed H. Alsamhi; Rafiqul Haque; Conor Judge; Edward Curry (IEEE Big Data, 2023)

Enabling Dataspaces Using Foundation Models: Technical, Legal and Ethical Considerations and Future Trends. - Mohan Timilsina; Samuele Buosi; Ping Song; Yang Yang 008; Rafiqul Haque; Edward Curry (IEEE Big Data, 2023)

Towards Graph-Based Semi-Supervised Learning on Audio Embeddings for Label Classification. - Rishabh Chandaliya; Mohan Timilsina; John G. Breslin; Martin Serrano (ICMLA, 2023)

Machine Learning Survival Models for Relapse Prediction in a Early Stage Lung Cancer Patient. - Mohan Timilsina; Samuele Buosi; Adrianna Janik; Pasquale Minervini; Luca Costabello; Maria Torrente; Mariano Provencio; Virginia Calvo; Carlos Camps; Ana L. Ortega; Bartomeu Massutí; M. Rosario Garcia Campelo; et al. (IJCNN, 2023)

Neural age screening on question answering communities. - Mohan Timilsina; Alejandro Figueroa 001 (Eng. Appl. Artif. Intell., 2023)

Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer. - Mohan Timilsina; Dirk Fey; Samuele Buosi; Adrianna Janik; Luca Costabello; Enric Carcereny; Delvys Rodriguez Abreu; Manuel Cobo; Rafael Castro; Reyes Bernabé; Pasquale Minervini; Maria Torrente; et al. (J. Biomed. Informatics, 2023)

BERT-Based Deep Learning for Classification of IgA Nephropathy, Diabetes, and Hypertension from Clinical Notes. - Samuele Buosi; Mohan Timilsina; Luke Harris; Sarah Monahan; Kieran Arthur; Niamh Corcoran; Nina Deacon; Michael Wrynn; Richard Farnan; David Keane; George Mellotte; Donal Reddan; et al. (BIBM, 2024)

Textual Pre-Trained Models for Age Screening Across Community Question-Answering. - Alejandro Figueroa 001; Mohan Timilsina (IEEE Access, 2024)

Empowering Dataspace 4.0: Unveiling Promise of Decentralized Data-Sharing. - Saeed Hamood Alsamhi; Ammar Hawbani; Santosh Kumar 006; Mohan Timilsina; Majjed Al-Qatf; Rafiqul Haque; Farhan M. A. Nashwan; Liang Zhao 004; Edward Curry (IEEE Access, 2024)

Boosting predictive models and augmenting patient data with relevant genomic and pathway information. - Samuele Buosi; Mohan Timilsina; Maria Torrente; Mariano Provencio; Dirk Fey; Vít Novácek (Comput. Biol. Medicine, 2024)

Machine learning estimated probability of relapse in early-stage non-small-cell lung cancer patients with aneuploidy imputation scores and knowledge graph embeddings. - Samuele Buosi; Mohan Timilsina; Adrianna Janik; Luca Costabello; Maria Torrente; Mariano Provencio; Dirk Fey; Vít Novácek (Expert Syst. Appl., 2024)

RAG4DS: Retrieval-Augmented Generation for Data Spaces - A Unified Lifecycle, Challenges, and Opportunities. - Majjed Al-Qatf; Rafiqul Haque; Saeed Hamood Alsamhi; Samuele Buosi; Muhammad Asif Razzaq; Mohan Timilsina; Ammar Hawbani; Edward Curry (IEEE Access, 2025)

Harmonizing foundation models in healthcare: A comprehensive survey of their roles, relationships, and impact in artificial intelligence's advancing terrain. - Mohan Timilsina; Samuele Buosi; Muhammad Asif Razzaq; Rafiqul Haque; Conor Judge; Edward Curry (Comput. Biol. Medicine, 2025)

Large language model vs. traditional machine learning: Evaluating predictive models for early detection of tumor relapse. - Mohan Timilsina; Samuele Buosi; Maria Torrente; Mariano Provencio; Manuel Cobo; Delvys Rodriguez Abreu; Rafael Castro; Enric Carcereny; Edward Curry; Vít Novácek (Expert Syst. Appl., 2025)