◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

M. Abbas

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • q-bio.QM2
  • q-bio.TO1
same name
  • M. Abbas — 3 papers
  • M. Abbas — 2 papers
  • M. Abbas — 1 paper, h 7
  • M. Abbas — 1 paper, h 22
  • M. Abbas — 1 paper
  • M. Abbas — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedDeep Learning for Prostate Pathology

1 citations · 1 across the 1 of their papers we have counts for

collaborators

3 papers

q-bio.TO2019★ 1 cited

Deep Learning for Prostate Pathology

Okyaz Eminaga, Yuri Tolkach, Christian Kunder +13

The current study detects different morphologies related to prostate pathology using deep learning models; these models were evaluated on 2,121 hematoxylin and eosin (H&E) stain hi…

q-bio.QM2019

Biologic and Prognostic Feature Scores from Whole-Slide Histology Images Using Deep Learning

Okyaz Eminaga, Mahmood Abbas, Yuri Tolkach +4

Histopathology is a reflection of the molecular changes and provides prognostic phenotypes representing the disease progression. In this study, we introduced feature scores generat…

q-bio.QM2019

Plexus Convolutional Neural Network (PlexusNet): A novel neural network architecture for histologic image analysis

Okyaz Eminaga, Mahmoud Abbas, Christian Kunder +5

Different convolutional neural network (CNN) models have been tested for their application in histological image analyses. However, these models are prone to overfitting due to the…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.