Development and validation of a deep learning model with enhanced explainability for interpreting melanocytic tumour pathologies. (#54)
Nigel G Maher
1
2
3
,
Xiaohang Fu
1
2
3
,
Emily L Clarke
4
5
,
Lucy Godson
4
6
,
Darren Treanor
4
5
7
,
Dianella Iglesias
8
,
Carla Daniela Robles-Espinoza
8
,
Héctor Martínez-Said
9
,
Richard A Scolyer
1
2
3
10
,
Ismael A Vergara
1
2
3
- Melanoma Institute Australia, Camperdown, NSW, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia
- Histopathology Department and National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
- Division of Pathology and Data Analytics, University of Leeds, Leeds, United Kingdom
- Leeds Institute of Medical Research, University of Leeds, Leeds, United Kingdom
- Departments of Clinical Pathology, and Clinical and Experimental Medicine and Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, Mexico
- Surgical Oncology, Skin, Soft Tissue & Bone Tumors Department, National Cancer Institute, Mexico City, Mexico
- Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, NSW, Australia