activity
20182021
most citedClassification of Histopathological Biopsy Images Using Ensemble of Deep Learning Networks

60 citations · 77 across the 6 of their papers we have counts for

collaborators

9 papers

cs.LG2021

Deep neural networks with controlled variable selection for the identification of putative causal genetic variants

Peyman H. Kassani, Fred Lu, Yann Le Guen +1

Deep neural networks (DNN) have been used successfully in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging…

eess.IV2020

Automatic Polyp Segmentation Using Convolutional Neural Networks

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski +2

Colorectal cancer is the third most common cancer-related death after lung cancer and breast cancer worldwide. The risk of developing colorectal cancer could be reduced by early di…

eess.IV2019★ 60 cited

Classification of Histopathological Biopsy Images Using Ensemble of Deep Learning Networks

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski +2

Breast cancer is one of the leading causes of death across the world in women. Early diagnosis of this type of cancer is critical for treatment and patient care. Computer-aided det…

eess.IV2019★ 2 cited

A Hybrid Deep Learning Architecture for Leukemic B-lymphoblast Classification

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh kassani, Michal J. Wesolowski +2

Automatic detection of leukemic B-lymphoblast cancer in microscopic images is very challenging due to the complicated nature of histopathological structures. To tackle this issue,…

eess.IV2019

Breast Cancer Diagnosis with Transfer Learning and Global Pooling

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski +2

Breast cancer is one of the most common causes of cancer-related death in women worldwide. Early and accurate diagnosis of breast cancer may significantly increase the survival rat…

cs.LG2019

k-Relevance Vectors: Considering Relevancy Beside Nearness

Sara Hosseinzadeh Kassani, Farhood Rismanchian, Peyman Hosseinzadeh Kassani

This study combines two different learning paradigms, k-nearest neighbor (k-NN) rule, as memory-based learning paradigm and relevance vector machines (RVM), as statistical learning…

cs.LG2019★ 1 cited

Multimodal Sparse Classifier for Adolescent Brain Age Prediction

Peyman Hosseinzadeh Kassani, Alexej Gossmann, Yu-Ping Wang

The study of healthy brain development helps to better understand the brain transformation and brain connectivity patterns which happen during childhood to adulthood. This study pr…

cs.IR2018★ 1 cited

Building an Ontology for the Domain of Plant Science using Protégé

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani

Due to the rapid development of technology, large amounts of heterogeneous data generated every day. Biological data is also growing in terms of the quantity and quality of data co…

cs.LG2018★ 13 cited

Introducing a hybrid model of DEA and data mining in evaluating efficiency. Case study: Bank Branches

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Seyed Esmaeel Najafi

The banking industry is very important for an economic cycle of each country and provides some quality of services for us. With the advancement in technology and rapidly increasing…