Fang‐I Lu - Concepedia

Author

Fang‐I Lu

Sunnybrook Health Science Centre ORCID

Also Known As

Benjamin Calhoun, F. Lu, F.-I. Lu, F.I. Lu, FANG-I LU, Fabrice Andre, Fang-I Lu, Fang-I. Lu, Fang‐I Lu, FuLei Lu

Publications

1.5K

Citations

H-Index

Concepts

All Affiliations

Sunnybrook Health Science Centre University of Toronto Health Sciences Centre York University Sunnybrook Research Institute

About

Fang‐I Lu is an author at Sunnybrook Health Science Centre specializing in medicine, oncology, and breast cancer.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Medicine	8	8	501
2	Engineering	3	3	124
3	Data Science	2	2	85
4	Gastroenterology	1	1	189
5	Mechanical Engineering	1	1	39

Fang‐I Lu

Publications

898

Citations

H-Index

Page 1

	Year	Citations
Longitudinal Outcome Study of Sessile Serrated Adenomas of the Colorectum: An Increased Risk for Subsequent Right-sided Colorectal Carcinoma Fang‐I Lu, De Wet van Niekerk, David Owen, The American Journal of Surgical Pathology Sessile Serrated AdenomasSurgical OncologyPossible SsasColorectal SurgeryMedicine	2010	189
Uterine Tumor Resembling Ovarian Sex Cord Tumor (UTROSCT) Emily A. Goebel, Silvia Hernandez Bonilla, Fei Dong, The American Journal of Surgical Pathology	2019	102
Comparative Analysis of Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer According to 2007 and 2013 American Society of Clinical Oncology/College of American Pathologists Guideline Recommendations Wedad Hanna, Elzbieta Slodkowska, Fang‐I Lu, Journal of Clinical Oncology Breast OncologyMedicineCancer GrowthPathologyAmerican Society	2017	75
Prevalence of Loss of Expression of DNA Mismatch Repair Proteins in Primary Epithelial Ovarian Tumors Fang‐I Lu, Cyril Blake Gilks, Anna Marie Mulligan, International Journal of Gynecological Pathology Genome InstabilityMedicinePathologyGynecologyMmr Protein Loss	2012	73
Fibroepithelial lesions of the breast: a comprehensive morphological and outcome analysis of a large series Elzbieta Slodkowska, Sharon Nofech‐Mozes, Bin Xu, Modern Pathology FibrosisComprehensive MorphologicalBreast OncologyLarge SeriesSurgical Pathology	2018	50
Machine Learning Frameworks to Predict Neoadjuvant Chemotherapy Response in Breast Cancer Using Clinical and Pathological Features Nicholas Meti, Khadijeh Saednia, Andrew Lagree, JCO Clinical Cancer Informatics	2021	50
Overcoming the limitations of patch-based learning to detect cancer in whole slide images Ozan Ciga, Tony Xu, Sharon Nofech‐Mozes, Scientific Reports Convolutional Neural NetworkMultiple Instance LearningEngineeringMachine LearningDigital Pathology	2021	46
Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies Khadijeh Saednia, Andrew Lagree, Marie Angeli Alera, Scientific Reports	2022	43
Quantitative Shear Wave Elastography Frederick Au, Sandeep Ghai, Fang‐I Lu, Academic Radiology Stress WaveOcean Wave MechanicsEngineeringMechanicsMechanical Engineering	2015	39
Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients David W. Dodington, Andrew Lagree, Sami Tabbarah, Breast Cancer Research and Treatment Artificial IntelligenceBreast OncologyEngineeringMachine LearningData Science	2021	39

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