One label is all you need: Interpretable AI-enhanced histopathology for oncology
Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to
benefit oncology through interpretable methods that require only one overall label per …
benefit oncology through interpretable methods that require only one overall label per …
A visual-language foundation model for computational pathology
The accelerated adoption of digital pathology and advances in deep learning have enabled
the development of robust models for various pathology tasks across a diverse array of …
the development of robust models for various pathology tasks across a diverse array of …
[HTML][HTML] Harnessing artificial intelligence for prostate cancer management
L Zhu, J Pan, W Mou, L Deng, Y Zhu, Y Wang… - Cell Reports …, 2024 - cell.com
Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is
crucial for clinical decision-making, but traditional pathology review is labor intensive and …
crucial for clinical decision-making, but traditional pathology review is labor intensive and …
Towards a visual-language foundation model for computational pathology
The accelerated adoption of digital pathology and advances in deep learning have enabled
the development of powerful models for various pathology tasks across a diverse array of …
the development of powerful models for various pathology tasks across a diverse array of …
[HTML][HTML] Contrastive multiple instance learning: An unsupervised framework for learning slide-level representations of whole slide histopathology images without …
Simple Summary Recent AI methods in the automated analysis of histopathological imaging
data associated with cancer have trended towards less supervision by humans. Yet, there …
data associated with cancer have trended towards less supervision by humans. Yet, there …
Learning how to detect: A deep reinforcement learning method for whole-slide melanoma histopathology images
Cutaneous melanoma represents one of the most life-threatening malignancies.
Histopathological image analysis serves as a vital tool for early melanoma detection. Deep …
Histopathological image analysis serves as a vital tool for early melanoma detection. Deep …
Probabilistic attention based on gaussian processes for deep multiple instance learning
A Schmidt, P Morales-Alvarez… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Multiple instance learning (MIL) is a weakly supervised learning paradigm that is becoming
increasingly popular because it requires less labeling effort than fully supervised methods …
increasingly popular because it requires less labeling effort than fully supervised methods …
An attention-based weakly supervised framework for spitzoid melanocytic lesion diagnosis in whole slide images
R Del Amor, L Launet, A Colomer, A Moscardó… - Artificial intelligence in …, 2021 - Elsevier
Melanoma is an aggressive neoplasm responsible for the majority of deaths from skin
cancer. Specifically, spitzoid melanocytic tumors are one of the most challenging …
cancer. Specifically, spitzoid melanocytic tumors are one of the most challenging …
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images
In the last years, the weakly supervised paradigm of multiple instance learning (MIL) has
become very popular in many different areas. A paradigmatic example is computational …
become very popular in many different areas. A paradigmatic example is computational …
[HTML][HTML] A deep learning model for prostate adenocarcinoma classification in needle biopsy whole-slide images using transfer learning
The histopathological diagnosis of prostate adenocarcinoma in needle biopsy specimens is
of pivotal importance for determining optimum prostate cancer treatment. Since diagnosing a …
of pivotal importance for determining optimum prostate cancer treatment. Since diagnosing a …