Smith, C.L.C.; Zwezerijnen, G.J.C.; Wiegers, S.E.; Jauw, Y.W.S.; Lugtenburg, P.J.; Zijlstra, J.M.; Yaqub, M.; Boellaard, R.
Feasibility of Using 18F-FDG PET/CT Radiomics and Machine Learning to Detect Drug-Induced Interstitial Lung Disease. Diagnostics 2024, 14, 2531.
https://doi.org/10.3390/diagnostics14222531
AMA Style
Smith CLC, Zwezerijnen GJC, Wiegers SE, Jauw YWS, Lugtenburg PJ, Zijlstra JM, Yaqub M, Boellaard R.
Feasibility of Using 18F-FDG PET/CT Radiomics and Machine Learning to Detect Drug-Induced Interstitial Lung Disease. Diagnostics. 2024; 14(22):2531.
https://doi.org/10.3390/diagnostics14222531
Chicago/Turabian Style
Smith, Charlotte L. C., Gerben J. C. Zwezerijnen, Sanne E. Wiegers, Yvonne W. S. Jauw, Pieternella J. Lugtenburg, Josée M. Zijlstra, Maqsood Yaqub, and Ronald Boellaard.
2024. "Feasibility of Using 18F-FDG PET/CT Radiomics and Machine Learning to Detect Drug-Induced Interstitial Lung Disease" Diagnostics 14, no. 22: 2531.
https://doi.org/10.3390/diagnostics14222531
APA Style
Smith, C. L. C., Zwezerijnen, G. J. C., Wiegers, S. E., Jauw, Y. W. S., Lugtenburg, P. J., Zijlstra, J. M., Yaqub, M., & Boellaard, R.
(2024). Feasibility of Using 18F-FDG PET/CT Radiomics and Machine Learning to Detect Drug-Induced Interstitial Lung Disease. Diagnostics, 14(22), 2531.
https://doi.org/10.3390/diagnostics14222531
