Modelling Airway Geometry as Stock Market Data Using Bayesian Changepoint Detection. - Kin Quan; Ryutaro Tanno; Michael Duong; Arjun Nair; Rebecca Shipley; Mark G. Jones; Christopher Brereton; John R. Hurst; David J. Hawkes; Joseph Jacob (MLMI@MICCAI, 2019)

Bayesian Sampling Bias Correction: Training with the Right Loss Function. - Loïc Le Folgoc; Vasileios Baltatzis; Amir Alansary; Sujal Desai; Anand Devaraj; Sam Ellis; Octavio E. Martinez Manzanera; Fahdi Kanavati; Arjun Nair; Julia A. Schnabel; Ben Glocker (CoRR, 2020)

Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data. - Octavio E. Martinez Manzanera; Sam Ellis; Vasileios Baltatzis; Arjun Nair; Loïc Le Folgoc; Sujal Desai; Ben Glocker; Julia A. Schnabel (ISBI, 2021)

The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. - Vasileios Baltatzis; Kyriaki-Margarita Bintsi; Loïc Le Folgoc; Octavio E. Martinez Manzanera; Sam Ellis; Arjun Nair; Sujal Desai; Ben Glocker; Julia A. Schnabel (PRIME@MICCAI, 2021)

The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. - Vasileios Baltatzis; Loïc Le Folgoc; Sam Ellis; Octavio E. Martinez Manzanera; Kyriaki-Margarita Bintsi; Arjun Nair; Sujal Desai; Ben Glocker; Julia A. Schnabel (iMIMIC/TDA4MedicalData@MICCAI, 2021)

A Computationally Efficient Approach to Segmentation of the Aorta and Coronary Arteries Using Deep Learning. - Wing Keung Cheung; Robert Bell; Arjun Nair; Leon J. Menezes; Riyaz Patel; Simon Wan; Kacy Chou; Jiahang Chen; Ryo Torii; Rhodri H. Davies; James C. Moon; Daniel C. Alexander; et al. (IEEE Access, 2021)

Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data. - Loïc Le Folgoc; Vasileios Baltatzis; Amir Alansary; Sujal Desai; Anand Devaraj; Sam Ellis; Octavio E. Martinez Manzanera; Fahdi Kanavati; Arjun Nair; Julia A. Schnabel; Ben Glocker (CoRR, 2021)

Is MC Dropout Bayesian? - Loïc Le Folgoc; Vasileios Baltatzis; Sujal Desai; Anand Devaraj; Sam Ellis; Octavio E. Martinez Manzanera; Arjun Nair; Huaqi Qiu; Julia A. Schnabel; Ben Glocker (CoRR, 2021)

STRUDEL: Structured Dialogue Summarization for Dialogue Comprehension. - Borui Wang; Chengcheng Feng; Arjun Nair; Madelyn Mao; Jai Desai; Asli Celikyilmaz; Haoran Li 007; Yashar Mehdad; Dragomir Radev (EMNLP, 2022)

CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning. - Xiangru Tang; Arjun Nair; Borui Wang; Bingyao Wang; Jai Desai; Aaron Wade; Haoran Li 007; Asli Celikyilmaz; Yashar Mehdad; Dragomir R. Radev (NAACL-HLT, 2022)

Enhancing Cancer Prediction in Challenging Screen-Detected Incident Lung Nodules Using Time-Series Deep Learning. - Shahab Aslani; Pavan Alluri; Eyjolfur Gudmundsson; Edward Chandy; John McCabe; Anand Devaraj; Carolyn Horst; Sam M. Janes; Rahul Chakkara; Arjun Nair; Daniel C. Alexander; SUMMIT Consortium; et al. (CoRR, 2022)

A 3D deep learning classifier and its explainability when assessing coronary artery disease. - Wing Keung Cheung; Jeremy Kalindjian; Robert Bell; Arjun Nair; Leon J. Menezes; Riyaz Patel; Simon Wan; Kacy Chou; Jiahang Chen; Ryo Torii; Rhodri H. Davies; James C. Moon; et al. (CoRR, 2023)

TimeSeAD: Benchmarking Deep Multivariate Time-Series Anomaly Detection. - Dennis Wagner; Tobias Michels; Florian C. F. Schulz; Arjun Nair; Maja Rudolph; Marius Kloft (Trans. Mach. Learn. Res., 2023)

Exploring Fairness in State-of-the-Art Pulmonary Nodule Detection Algorithms. - John McCabe; Daryl Cheng; Amyn Bhamani; Monica Mullin; Tanya Patrick; Arjun Nair; Sam M. Janes; Carole H. Sudre; Joseph Jacob (FAIMI/EPIMI@MICCAI, 2024)

Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning. - Shahab Aslani; Pavan Alluri; Eyjolfur Gudmundsson; Edward Chandy; John McCabe; Anand Devaraj; Carolyn Horst; Sam M. Janes; Rahul Chakkara; Daniel C. Alexander; Arjun Nair; Joseph Jacob (Comput. Medical Imaging Graph., 2024)