# Image Classification of Stroke Blood Clot Origin using Deep Convolutional Neural Networks and Visual Transformers

Source: [Image Classification of Stroke Blood Clot Origin using Deep Convolutional Neural Networks and Visual Transformers](<https://www.sota2.com/research/paper/68fa6f801e209131cea46033>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:21:27.030Z

Authors: David Azatyan

Published: 2023-05-25T21:46:12.000Z

## Abstract

Stroke is one of two main causes of death worldwide. Many individuals suffer from ischemic stroke every year. Only in US more over 700,000 individuals meet ischemic stroke due to blood clot blocking an artery to the brain every year. The paper describes particular approach how to apply Artificial Intelligence for purposes of separating two major acute ischemic stroke (AIS) etiology subtypes: cardiac and large artery atherosclerosis. Four deep neural network architectures and simple ensemble method are used in the approach.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2305.16492>)

[PDF](<https://arxiv.org/pdf/2305.16492.pdf>)