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[HTML][HTML] Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
D Nam, J Chapiro, V Paradis, TP Seraphin, JN Kather - Jhep Reports, 2022 - Elsevier
Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …
Artificial intelligence to identify genetic alterations in conventional histopathology
Precision oncology relies on the identification of targetable molecular alterations in tumor
tissues. In many tumor types, a limited set of molecular tests is currently part of standard …
tissues. In many tumor types, a limited set of molecular tests is currently part of standard …
Swarm learning for decentralized artificial intelligence in cancer histopathology
OL Saldanha, P Quirke, NP West, JA James… - Nature medicine, 2022 - nature.com
Artificial intelligence (AI) can predict the presence of molecular alterations directly from
routine histopathology slides. However, training robust AI systems requires large datasets …
routine histopathology slides. However, training robust AI systems requires large datasets …
Adversarial attacks and adversarial robustness in computational pathology
N Ghaffari Laleh, D Truhn, GP Veldhuizen… - Nature …, 2022 - nature.com
Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis
and providing biomarkers directly from routine pathology slides. However, AI applications …
and providing biomarkers directly from routine pathology slides. However, AI applications …
Encrypted federated learning for secure decentralized collaboration in cancer image analysis
D Truhn, ST Arasteh, OL Saldanha… - Medical image …, 2024 - Elsevier
Artificial intelligence (AI) has a multitude of applications in cancer research and oncology.
However, the training of AI systems is impeded by the limited availability of large datasets …
However, the training of AI systems is impeded by the limited availability of large datasets …
Slideflow: deep learning for digital histopathology with real-time whole-slide visualization
JM Dolezal, S Kochanny, E Dyer, S Ramesh… - BMC …, 2024 - Springer
Deep learning methods have emerged as powerful tools for analyzing histopathological
images, but current methods are often specialized for specific domains and software …
images, but current methods are often specialized for specific domains and software …
[HTML][HTML] Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer
N Zamanitajeddin, M Jahanifar, M Bilal… - Medical Image …, 2024 - Elsevier
Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …
DeepMed: a unified, modular pipeline for end-to-end deep learning in computational pathology
M van Treeck, D Cifci, NG Laleh, OL Saldanha… - BioRxiv, 2021 - biorxiv.org
The interpretation of digitized histopathology images has been transformed thanks to
artificial intelligence (AI). End-to-end AI algorithms can infer high-level features directly from …
artificial intelligence (AI). End-to-end AI algorithms can infer high-level features directly from …
[HTML][HTML] Artificial intelligence-based multi-class histopathologic classification of kidney neoplasms
DD Gondim, KI Al-Obaidy, MT Idrees, JN Eble… - Journal of Pathology …, 2023 - Elsevier
Artificial intelligence (AI)-based techniques are increasingly being explored as an emerging
ancillary technique for improving accuracy and reproducibility of histopathological …
ancillary technique for improving accuracy and reproducibility of histopathological …
End-to-end learning for image-based detection of molecular alterations in digital pathology
M Teichmann, A Aichert, H Bohnenberger… - … Conference on Medical …, 2022 - Springer
Current approaches for classification of whole slide images (WSI) in digital pathology
predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest …
predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest …