Published on in Vol 22, No 4 (2020): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16533, first published .
Optimizing the Analytical Value of Oncology-Related Data Based on an In-Memory Analysis Layer: Development and Assessment of the Munich Online Comprehensive Cancer Analysis Platform

Optimizing the Analytical Value of Oncology-Related Data Based on an In-Memory Analysis Layer: Development and Assessment of the Munich Online Comprehensive Cancer Analysis Platform

Optimizing the Analytical Value of Oncology-Related Data Based on an In-Memory Analysis Layer: Development and Assessment of the Munich Online Comprehensive Cancer Analysis Platform

Journals

  1. Sellmer L, Kovács J, Neumann J, Walter J, Kauffmann-Guerrero D, Syunyaeva Z, Fertmann J, Schneider C, Zimmermann J, Behr J, Tufman A. Lymphocytes and Sinus Histiocytosis in Tumor and Matched Lymph Nodes As Predictors of Survival in Non-Small-Cell Lung Cancer. Future Oncology 2022;18(4):481 View
  2. Kasprzak J, Frey S, Oetlinger H, Benedikt Westphalen C, Erickson N, Heinemann V, Nasseh D. Swapping data: A pragmatic approach for enabling academic-industrial partnerships. DIGITAL HEALTH 2023;9:205520762311721 View
  3. Tufman A, Schneiderbauer S, Walter J, Resuli B, Kauffmann-Guerrero D, Mümmler C, Mertsch P, Götschke J, Kovács J, Manapov F, Schneider C, Sellmer L, Arnold P, Heinemann V, Behr J, Nasseh D. Early mortality in German patients with lung cancer: risk factors associated with 30-and 60-day mortality. Clinical and Experimental Medicine 2023;23(8):5183 View
  4. Kasprzak J, Westphalen C, Frey S, Schmitt Y, Heinemann V, Fey T, Nasseh D. Supporting the decision to perform molecular profiling for cancer patients based on routinely collected data through the use of machine learning. Clinical and Experimental Medicine 2024;24(1) View