J. Dinny Graham
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View article: Supplementary Figure 9 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 9 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Feature importance for selected proteins with utility at distinguishing cancer subtypes
View article: Table S4 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Table S4 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Per class AUROC using ProCan Compendium and external datasets
View article: Supplementary Figure 11 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 11 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Pathway analysis of top SHAP-ranked proteins across cancer subtypes
View article: Supplementary Figure 10 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 10 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Cell type enrichment analysis of top SHAP-ranked proteins across cancer subtypes
View article: Table S5 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Table S5 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Feature importance for cancer subtype prediction using SHAP.
View article: Table S2 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Table S2 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Per class AUROC for models using ProCan Compendium
View article: Supplementary Figure 2 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 2 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Overview of Cohort 1
View article: Supplementary Figure 8 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 8 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Effects of adding external datasets
View article: Supplementary Figure 7 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 7 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
ProCanFDL with external datasets
View article: Supplementary Figure 3 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 3 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Distributions of Cancer Subtypes in Cohort 1 and ProCan Compendium for ProCanFDL
View article: Supplementary Figure 1 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 1 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Overview of ProCan Compendium
View article: Supplementary Figure 6 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 6 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
ProCanFDL of ProCan Compendium
View article: Supplementary Figure 5 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 5 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Sample sizes of Sites 1-4 across ten experiments
View article: Supplementary Figure 4 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 4 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Distribution of cancer subtypes across Sites 2-4 and Experiments 1-10
View article: Supplementary Figure 12 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 12 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Protein overlap between global and local models based on SHAP rankings
View article: Supplementary Figure 13 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Supplementary Figure 13 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
SHAP values of antibody drug conjugate targets across cancer subtypes
View article: Data from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Data from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a federated deep learning approach (ProCanFDL), tr…
View article: Table S1 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Table S1 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Cohort details of ProCan Compendium
View article: Table S3 from Federated Deep Learning Enables Cancer Subtyping by Proteomics
Table S3 from Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Per class AUROC for models using ProCan Compendium
View article: Spatial gene expression at single-cell resolution from histology using deep learning with GHIST
Spatial gene expression at single-cell resolution from histology using deep learning with GHIST Open
The increased use of spatially resolved transcriptomics provides new biological insights into disease mechanisms. However, the high cost and complexity of these methods are barriers to broader application. Consequently, methods have been c…
View article: Federated Deep Learning Enables Cancer Subtyping by Proteomics
Federated Deep Learning Enables Cancer Subtyping by Proteomics Open
Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a federated deep learning approach (ProCanFDL), tr…
View article: 8770 Highly Multiplexed Mapping of the Ductal Carcinoma In Situ Ecosystem to Predict Disease Outcome
8770 Highly Multiplexed Mapping of the Ductal Carcinoma In Situ Ecosystem to Predict Disease Outcome Open
Disclosure: G.M. Wilson: None. T.B. Doan: None. B.J. Guild: None. N. Pathmanathan: None. J.D. Graham: None. Mammographic screening programs have resulted in remarkable improvements in breast cancer survival due to early-stage detection. Ho…
View article: 9218 Highly Multiplexed Mapping Of The Ductal Carcinoma In Situ Ecosystem To Predict Disease Outcome
9218 Highly Multiplexed Mapping Of The Ductal Carcinoma In Situ Ecosystem To Predict Disease Outcome Open
Disclosure: G.M. Wilson: None. T.B. Doan: None. B.J. Guild: None. N. Pathmanathan: None. J.D. Graham: None. Mammographic screening programs have resulted in remarkable improvements in breast cancer survival due to early-stage detection. Ho…
View article: 9218 Highly Multiplexed Mapping of the Ductal Carcinoma In Situ Ecosystem to Predict Disease Outcome
9218 Highly Multiplexed Mapping of the Ductal Carcinoma In Situ Ecosystem to Predict Disease Outcome Open
Disclosure: G.M. Wilson: None. T.B. Doan: None. B.J. Guild: None. N. Pathmanathan: None. J.D. Graham: None. Mammographic screening programs have resulted in remarkable improvements in breast cancer survival due to early-stage detection. Ho…
View article: 8770 Highly Multiplexed Mapping Of The Ductal Carcinoma In Situ Ecosystem To Predict Disease Outcome
8770 Highly Multiplexed Mapping Of The Ductal Carcinoma In Situ Ecosystem To Predict Disease Outcome Open
Disclosure: G.M. Wilson: None. T.B. Doan: None. B.J. Guild: None. N. Pathmanathan: None. J.D. Graham: None. Mammographic screening programs have resulted in remarkable improvements in breast cancer survival due to early-stage detection. Ho…
View article: The multifaceted role of the mineralocorticoid receptor in cancers
The multifaceted role of the mineralocorticoid receptor in cancers Open
The mineralocorticoid receptor (MR/NR3C2) is a member of the family of steroid receptors (SR) which also includes the estrogen receptor (ER), progesterone receptor (PR), androgen receptor (AR) and glucocorticoid receptor (GR). They functio…
View article: PDGF-AB Reduces Myofibroblast Differentiation Without Increasing Proliferation After Myocardial Infarction
PDGF-AB Reduces Myofibroblast Differentiation Without Increasing Proliferation After Myocardial Infarction Open
After myocardial infarction (MI), fibroblasts progress from proliferative to myofibroblast states, resulting in fibrosis. Platelet-derived growth factors (PDGFs) are reported to induce fibroblast proliferation, myofibroblast differentiatio…
View article: Artificial intelligence‐based digital scores of stromal tumour‐infiltrating lymphocytes and tumour‐associated stroma predict disease‐specific survival in triple‐negative breast cancer
Artificial intelligence‐based digital scores of stromal tumour‐infiltrating lymphocytes and tumour‐associated stroma predict disease‐specific survival in triple‐negative breast cancer Open
Triple‐negative breast cancer (TNBC) is known to have a relatively poor outcome with variable prognoses, raising the need for more informative risk stratification. We investigated a set of digital, artificial intelligence (AI)‐based spatia…
View article: Tropoelastin Improves Post-Infarct Cardiac Function
Tropoelastin Improves Post-Infarct Cardiac Function Open
Background: Myocardial infarction (MI) is among the leading causes of death worldwide. Following MI, necrotic cardiomyocytes are replaced by a stiff collagen-rich scar. Compared to collagen, the extracellular matrix protein elastin has hig…
View article: Ductal Carcinoma in Situ: Molecular Changes Accompanying Disease Progression
Ductal Carcinoma in Situ: Molecular Changes Accompanying Disease Progression Open