Junaid Latief Shah

Radiology, Nuclear Medicine and Imaging · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Radiology, Nuclear Medicine and Imaging — 13 citations into it; #2,184 of 3,265 by trust here, #2,536 by citations
• Computer Vision and Pattern Recognition — 9 citations into it; #17,404 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 8 citations into it
• Infectious Diseases — 6 citations into it; #319 of 589 by trust here, #457 by citations

Whom Junaid Latief Shah trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. François Chollet
2. Linda Wang
3. T. Ozturk

Who trusts Junaid Latief Shah overall

1. Ali Narin
2. Muhammet Fatih Aslan

Papers from Junaid Latief Shah's perspective

Ordered by how strongly the researchers Junaid Latief Shah trusts endorse each paper. Same corpus, a different order for every researcher.

1. Xception: Deep Learning with Depthwise Separable Convolutions
2. CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
3. COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
4. Deep Learning in Medical Image Analysis
5. Coronavirus covid-19 has killed more people than SARS and MERS combined, despite lower case fatality rate (British medical journal)
6. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR (Radiology)
7. Pattern classification, 2nd Edition
8. Deep Learning for Content-Based Image Retrieval: A Comprehensive Study (ACM Multimedia)
9. Automated detection of COVID-19 cases using deep neural networks with X-ray images (Comput. Biol. Medicine)
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images (2020) — 1,161 citations