6 citations · 6 across the 2 of their papers we have counts for
3 papers
eess.IV2021
Advancement of Deep Learning in Pneumonia and Covid-19 Classification and Localization: A Qualitative and Quantitative Analysis
Aakash Shah, Manan Shah
Around 450 million people are affected by pneumonia every year which results in 2.5 million deaths. Covid-19 has also affected 181 million people which has lead to 3.92 million cas…
cs.CV2018
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
Mitko Veta, Yujing J. Heng, Nikolas Stathonikos +30
Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is highly subjective an…
cs.CV2016★ 6 cited
Deep Learning Assessment of Tumor Proliferation in Breast Cancer Histological Images
Manan Shah, Christopher Rubadue, David Suster +1
Current analysis of tumor proliferation, the most salient prognostic biomarker for invasive breast cancer, is limited to subjective mitosis counting by pathologists in localized re…