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Medicine 논문 리뷰
Medicine 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
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필터
4,880개의 결과
BrainSegNet : A Segmentation Network for Human Brain Fiber Tractography Data into Anatomically Meaningful Clusters
Tushar Gupta, Shreyas Malakarjun Patil 외 3명
arXiv (Cornell University)
|
2017
|
8 회 인용
Breast Cancer Segmentation using Attention-based Convolutional Network and Explainable AI
Jai Vardhan, Ghanta Sai Krishna
arXiv (Cornell University)
|
2023
|
8 회 인용
BUSU-Net: An Ensemble U-Net Framework for Medical Image Segmentation
Wei Hao Khoong
arXiv (Cornell University)
|
2020
|
8 회 인용
Can artificial intelligence (AI) be used to accurately detect tuberculosis (TB) from chest x-ray? A multiplatform evaluation of five AI products used for TB screening in a high TB-burden setting.
Zhi Zhen Qin, Shahriar Ahmed 외 6명
arXiv (Cornell University)
|
2020
|
8 회 인용
Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction?
Mohammad Zalbagi Darestani, Reinhard Heckel
arXiv (Cornell University)
|
2020
|
8 회 인용
Cardiomegaly Detection using Deep Convolutional Neural Network with U-Net
Soham S. Sarpotdar
arXiv (Cornell University)
|
2022
|
8 회 인용
Cartesian Neural Network Constitutive Models for Data-driven Elasticity Imaging
Cameron Hoerig, Jamshid Ghaboussi 외 1명
arXiv (Cornell University)
|
2018
|
8 회 인용
Caveats in Generating Medical Imaging Labels from Radiology Reports
Tobi Olatunji, Yao Li 외 3명
arXiv (Cornell University)
|
2019
|
8 회 인용
CHS-Net: A Deep learning approach for hierarchical segmentation of COVID-19 infected CT images
Narinder Singh Punn, Sonali Agarwal
arXiv (Cornell University)
|
2020
|
8 회 인용
Classification of Diabetic Retinopathy via Fundus Photography: Utilization of Deep Learning Approaches to Speed up Disease Detection
Hangwei Zhuang, Nabil Ettehadi
arXiv (Cornell University)
|
2020
|
8 회 인용
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