A Personalised Monitoring and Recommendation Framework for Kinetic Dysfunctions: The Trendelenburg Gait. - Nikolaos Michalopoulos; George E. Raptis; Christina P. Katsini; Theofilos Chrysikos; Michail Mamalakis; Andrew Vigotsky (PCI, 2016)

MA-SOCRATIS: An automatic pipeline for robust segmentation of the left ventricle and scar. - Michail Mamalakis; Pankaj Garg; Tom Nelson; Justin Lee; Jim M. Wild; Richard H. Clayton (Comput. Medical Imaging Graph., 2021)

DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. - Michail Mamalakis; Andrew J. Swift; Bart Vorselaars; Surajit Ray; Simonne Weeks; Weiping Ding 001; Richard H. Clayton; Louise S. Mackenzie; Abhirup Banerjee (Comput. Medical Imaging Graph., 2021)

Automatic development of 3D anatomical models of border zone and core scar regions in the left ventricle. - Michail Mamalakis; Pankaj Garg; Tom Nelson; Justin Lee; Andrew J. Swift; Jim M. Wild; Richard H. Clayton (Comput. Medical Imaging Graph., 2023)

A 3D explainability framework to uncover learning patterns and crucial sub-regions in variable sulci recognition. - Michail Mamalakis; Héloïse de Vareilles; Atheer AI-Manea; Samantha C. Mitchell; Ingrid Agartz; Lynn Egeland Morch-Johnsen; Jane R. Garrison; Jon S. Simons; Pietro Lio; John Suckling; Graham K. Murray (CoRR, 2023)

A novel framework employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy. - Michail Mamalakis; Sarah C. Macfarlane; Scott V. Notley; Annica K. B. Gad; George Panoutsos (CoRR, 2023)

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge. - Yang Nan 002; Xiaodan Xing; Shiyi Wang; Zeyu Tang 001; Federico N. Felder; Sheng Zhang 024; Roberta Eufrasia Ledda; Xiaoliu Ding; Ruiqi Yu; Weiping Liu; Feng Shi 001; Tianyang Sun; et al. (CoRR, 2023)

Artificial Intelligence framework with traditional computer vision and deep learning approaches for optimal automatic segmentation of left ventricle with scar. - Michail Mamalakis; Pankaj Garg; Tom Nelson; Justin Lee; Andrew J. Swift; James M. Wild; Richard H. Clayton (Artif. Intell. Medicine, 2023)

A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding. - Yiqing Shen 003; Zan Chen; Michail Mamalakis; Luhan He; Haiyang Xia; Tianbin Li; Yanzhou Su; Junjun He; Yu Guang Wang 001 (BIBM, 2024)

TourSynbio: A Multi-Modal Large Model and Agent Framework to Bridge Text and Protein Sequences for Protein Engineering. - Yiqing Shen 003; Zan Chen; Michail Mamalakis; Yungeng Liu; Tianbin Li; Yanzhou Su; Junjun He; Pietro Liò; Yu Guang Wang 001 (BIBM, 2024)

A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy. - Michail Mamalakis; Sarah C. Macfarlane; Scott V. Notley; Annica K. B. Gad; George Panoutsos (Comput. Biol. Medicine, 2024)

Solving the enigma: Deriving optimal explanations of deep networks. - Michail Mamalakis; Antonios Mamalakis; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Graham K. Murray; John Suckling; Pietro Lio (CoRR, 2024)

Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification. - Michail Mamalakis; Héloïse de Vareilles; Shun-Chin Jim Wu; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Jane R. Garrison; Jon S. Simons; Pietro Lio; John Suckling; Graham K. Murray (CoRR, 2024)

The Explanation Necessity for Healthcare AI. - Michail Mamalakis; Héloïse de Vareilles; Graham K. Murray; Pietro Lio; John Suckling (CoRR, 2024)

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge. - Yang Nan 002; Xiaodan Xing; Shiyi Wang; Zeyu Tang 001; Federico N. Felder; Sheng Zhang 024; Roberta Eufrasia Ledda; Xiaoliu Ding; Ruiqi Yu; Weiping Liu; Feng Shi 001; Tianyang Sun; et al. (Medical Image Anal., 2024)

Deep multi-metric training: the need of multi-metric curve evaluation to avoid weak learning. - Michail Mamalakis; Abhirup Banerjee; Surajit Ray; Craig Wilkie; Richard H. Clayton; Andrew J. Swift; George Panoutsos; Bart Vorselaars (Neural Comput. Appl., 2024)

Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks. - Michail Mamalakis; Antonios Mamalakis; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Graham K. Murray; John Suckling; Pietro Lio (AI Open, 2025)

Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods. - Carmen Jimenez-Mesa; Yizhou Wan; Guilio Sansone; Francisco Jesús Martínez-Murcia; Javier Ramírez 001; Pietro Lio; Juan Manuel Górriz; Stephen J. Price; John Suckling; Michail Mamalakis (CoRR, 2025)