Michail Mamalakis

According to our database, Michail Mamalakis authored at least 16 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., October, 2024

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Yang Nan, Xiaodan Xing, Shiyi Wang, Zeyu Tang, Federico N. Felder, Sheng Zhang, Roberta Eufrasia Ledda, Xiaoliu Ding, Ruiqi Yu, Weiping Liu, Feng Shi, Tianyang Sun, Zehong Cao, Minghui Zhang, Yun Gu, Hanxiao Zhang, Jian Gao, Pingyu Wang, Wen Tang, Pengxin Yu, Han Kang, Junqiang Chen, Xing Lu, Boyu Zhang, Michail Mamalakis, Francesco Prinzi, Gianluca Carlini, Lisa Cuneo, Abhirup Banerjee, Zhaohu Xing, Lei Zhu, Zacharia Mesbah, Dhruv Jain, Tsiry Mayet, Hongyu Yuan, Qing Lyu, Abdul Qayyum, Moona Mazher, Athol Wells, Simon L. F. Walsh, Guang Yang

Medical Image Anal., 2024

TourSynbio: A Multi-Modal Large Model and Agent Framework to Bridge Text and Protein Sequences for Protein Engineering.

Yiqing Shen, Zan Chen, Michail Mamalakis, Yungeng Liu, Tianbin Li, Yanzhou Su, Junjun He, Pietro Liò, Yu Guang Wang

CoRR, 2024

A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding.

Yiqing Shen, Zan Chen, Michail Mamalakis, Luhan He, Haiyang Xia, Tianbin Li, Yanzhou Su, Junjun He, Yu Guang Wang

CoRR, 2024

The Explanation Necessity for Healthcare AI.

Michail Mamalakis, Héloïse de Vareilles, Graham K. Murray, Pietro Lio, John Suckling

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

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

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

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, September, 2023

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Yang Nan, Xiaodan Xing, Shiyi Wang, Zeyu Tang, Federico N. Felder, Sheng Zhang, Roberta Eufrasia Ledda, Xiaoliu Ding, Ruiqi Yu, Weiping Liu, Feng Shi, Tianyang Sun, Zehong Cao, Minghui Zhang, Yun Gu, Hanxiao Zhang, Jian Gao, Wen Tang, Pengxin Yu, Han Kang, Junqiang Chen, Xing Lu, Boyu Zhang, Michail Mamalakis, Francesco Prinzi, Gianluca Carlini, Lisa Cuneo, Abhirup Banerjee, Zhaohu Xing, Lei Zhu, Zacharia Mesbah, Dhruv Jain, Tsiry Mayet, Hongyu Yuan, Qing Lyu, Athol Wells, Simon Walsh, Guang Yang

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

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

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

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, Richard H. Clayton, Louise S. Mackenzie, Abhirup Banerjee

Comput. Medical Imaging Graph., 2021

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

2016

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

Proceedings of the 20th Pan-Hellenic Conference on Informatics, 2016