Sandhya Prabhakaran
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Sandhya Prabhakaran has a total of 397 co-authors. Here are the top co-authors by number of shared publications:
- Alexander R. A. Anderson
Moffitt Cancer Center 1 Tampa, FL
80 shared publications - Chandler D. Gatenbee
H. Lee Moffitt Cancer Center & Research Institute
61 shared publications - Mark Robertson-Tessi
Integrated Mathematical Oncology (IMO) Department, Moffitt Cancer Center, Tampa, FL 33612L, USA
55 shared publications - Robert A. Gatenby
Moffitt Cancer Center
52 shared publications - Jhanelle Elaine Gray
Department of Thoracic Oncology, Moffitt Cancer Center, Tampa, FL 33612, USA
51 shared publications - Theresa A. Boyle
Moffitt Cancer Center 4 Department of Pathology Tampa, Florida
50 shared publications
Latest Publications
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary_Table_2 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Supplementary Table 2 shows different metastatic sites used for biopsy collection in this study.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary_Table_2 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Supplementary Table 2 shows different metastatic sites used for biopsy collection in this study.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary_Table_3 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Supplementary Table 3 describes the classification statistics using LOOCV for SVM and NN SDM based on the number of patients correctly classified.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary_Table_3 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Supplementary Table 3 describes the classification statistics using LOOCV for SVM and NN SDM based on the number of patients correctly classified.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S5 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S5 shows the RoGM analysis for the non-spatial setting.
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S5 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S5 shows the RoGM analysis for the non-spatial setting.
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S4 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S4 describes the statistical 'difference network analysis'
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S4 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S4 describes the statistical 'difference network analysis'
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S8 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S8 describes bar plots for area normalized cell counts across SD and PD patients, pre and during treatment, for each cellular/quadrat neighborhood
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S8 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S8 describes bar plots for area normalized cell counts across SD and PD patients, pre and during treatment, for each cellular/quadrat neighborhood
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S6 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S6 depicts the NN SDM architecture
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S6 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S6 depicts the NN SDM architecture
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S6 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S6 depicts the NN SDM architecture
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S6 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S6 depicts the NN SDM architecture
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S1 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S1 describes the image processing pipeline and convex hull analysis
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S1 from Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response
Figure S1 describes the image processing pipeline and convex hull analysis