Independent assessment of a deep learning system for lymph node metastasis detection on the Augmented Reality Microscope
Several machine learning algorithms have demonstrated high predictive capability in the identification of cancer within digitized pathology slides. The Augmented Reality Microscope (ARM) has allowed these algorithms to be seamlessly integrated within the pathology workflow by overlaying their infere...
Saved in:
Main Authors: | David Jin (Author), Joseph H. Rosenthal (Author), Elaine E. Thompson (Author), Jared Dunnmon (Author), Arash Mohtashamian (Author), Daniel Ward (Author), Ryan Austin (Author), Hassan Tetteh (Author), Niels H. Olson (Author) |
---|---|
Format: | Book |
Published: |
Elsevier,
2022-01-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Independent risk factors for axillary lymph node metastasis in breast cancer patients with one or two positive sentinel lymph nodes
by: Wei Zhang, et al.
Published: (2020) -
Targeting Lymph Node Sinus Macrophages to Inhibit Lymph Node Metastasis
by: Junqing Hu, et al.
Published: (2019) -
Cervical lymph node metastasis of porocarcinoma
by: Philipp Becker, et al.
Published: (2021) -
Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review
by: Elzbieta Budginaite, et al.
Published: (2024) -
Cervical lymph node metastasis in oral squamous cell carcinoma: A correlative study between histopathological malignancy grading and lymph node metastasis
by: Swetha Acharya, et al.
Published: (2013)