Jamen Bartlett
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View article: LINE‐1 Retroelement Activation and Neuroinflammation in Persons With Fanconi Anemia
LINE‐1 Retroelement Activation and Neuroinflammation in Persons With Fanconi Anemia Open
We describe the first immunohistochemical analysis performed on brain lesion biopsies from two young individuals with Fanconi anemia neuroinflammatory syndrome (FANS). We identified aberrant activation of the LINE‐1 retrotransposon as a no…
View article: Tryptophan metabolism is dysregulated in individuals with Fanconi anemia
Tryptophan metabolism is dysregulated in individuals with Fanconi anemia Open
Fanconi anemia (FA) is a complex genetic disorder associated with progressive marrow failure and a strong predisposition to malignancy. FA is associated with metabolic disturbances such as short stature, insulin resistance, thyroid dysfunc…
View article: MLCD: A Unified Software Package for Cancer Diagnosis
MLCD: A Unified Software Package for Cancer Diagnosis Open
PURPOSE Machine Learning Package for Cancer Diagnosis (MLCD) is the result of a National Institutes of Health/National Cancer Institute (NIH/NCI)-sponsored project for developing a unified software package from state-of-the-art breast canc…
View article: Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions
Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions Open
The computer-based automated approach to interpreting breast pathology showed promise, especially as a diagnostic aid in differentiating DCIS from atypical hyperplasia.
View article: Y-Net: Joint Segmentation and Classification for Diagnosis of Breast\n Biopsy Images
Y-Net: Joint Segmentation and Classification for Diagnosis of Breast\n Biopsy Images Open
In this paper, we introduce a conceptually simple network for generating\ndiscriminative tissue-level segmentation masks for the purpose of breast cancer\ndiagnosis. Our method efficiently segments different types of tissues in breast\nbio…
View article: Learning to Segment Breast Biopsy Whole Slide Images
Learning to Segment Breast Biopsy Whole Slide Images Open
We trained and applied an encoder-decoder model to semantically segment breast biopsy images into biologically meaningful tissue labels. Since conventional encoder-decoder networks cannot be applied directly on large biopsy images and the …