Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance.

M. Mazurowski, P. Habas, J. Zurada, J. Lo, J. Baker, and G. Tourassi. Neural Networks, 21 (2-3): 427-436 (2008)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Vivien Lo

Wingkwong Lo

Edward Lo

Hanna Lo

Stephanie Lo

Other publications of authors with the same name

Self-organizing map for cluster analysis of a breast cancer database.M. Markey, J. Lo, G. Tourassi, and C. Jr.. Artif. Intell. Medicine, 27 (2): 113-127 (2003)Development and Application of a Suite of 4-D Virtual Breast Phantoms for Optimization and Evaluation of Breast Imaging Systems.N. Kiarashi, J. Lo, Y. Lin, L. Ikejimba, S. Ghate, L. Nolte, J. Dobbins, W. Segars, and E. Samei. IEEE Trans. Medical Imaging, 33 (7): 1401-1409 (2014)Ipsilateral Lesion Detection Refinement for Tomosynthesis.Y. Ren, X. Liu, J. Ge, Z. Liang, X. Xu, L. Grimm, J. Go, J. Marks, and J. Lo. IEEE Trans. Medical Imaging, 42 (10): 3080-3090 (October 2023)Weakly Supervised Multi-Organ Multi-Disease Classification of Body CT Scans.F. Tushar, V. D'Anniballe, R. Hou, M. Mazurowski, W. Fu, E. Samei, G. Rubin, and J. Lo. CoRR, (2020)Self-organizing maps for analyzing mammographic findings.J. Lo, and C. Jr.. ICNN, page 2472-2474. IEEE, (1997)Data diversity and virtual imaging in AI-based diagnosis: A case study based on COVID-19.F. Tushar, L. Dahal, S. Sotoudeh-Paima, E. Abadi, W. Segars, E. Samei, and J. Lo. CoRR, (2023)Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CT.F. Tushar, V. D'Anniballe, G. Rubin, E. Samei, and J. Lo. Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)Application of a new evolutionary programming/adaptive boosting hybrid to breast cancer diagnosis.W. Jr., T. Masters, and J. Lo. CEC, page 1436-1442. IEEE, (2000)Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance.M. Mazurowski, P. Habas, J. Zurada, J. Lo, J. Baker, and G. Tourassi. Neural Networks, 21 (2-3): 427-436 (2008)Computer-aided diagnosis of mammography using an artificial neural network: predicting the invasiveness of breast cancers from image features.J. Lo, J. Kim, J. Baker, and C. Jr.. Medical Imaging: Image Processing, volume 2710 of SPIE Proceedings, SPIE, (1996)

BibSonomy

Disambiguation of "Lo, Joseph Y."

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance.

Please choose a person to relate this publication to

Vivien Lo

Wingkwong Lo

Edward Lo

Hanna Lo

Stephanie Lo

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Lo, Joseph Y."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance.

Please choose a person to relate this publication to

Vivien Lo

Wingkwong Lo

Edward Lo

Hanna Lo

Stephanie Lo

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance.