arXiv:1906.11282
공식 코드 · Papers with Code
Developing an App to interpret Chest X-rays to support the diagnosis of respiratory pathology with Artificial Intelligence
원문 초록
In this paper we present our work to improve access to diagnosis in remote areas where good quality medical services may be lacking. We develop new Machine Learning methodologies for deployment onto mobile devices to help the early diagnosis of a number of life-threatening conditions using X-ray images. By using the latest developments in fast and portable Artificial Intelligence environments, we develop a smartphone app using an Artificial Neural Network to assist physicians in their diagnostic.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ResCovNet: A Deep Learning-Based Architecture For COVID-19 Detection From Chest CT Scan Images
A Cytology Dataset for Early Detection of Oral Squamous Cell Carcinoma
AI-Enhanced Pediatric Pneumonia Detection: A CNN-Based Approach Using Data Augmentation and Generative Adversarial Networks (GANs)
LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models
Hybrid-View Attention for csPCa Classification in TRUS
Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding
토론
이 논문과 연결된 포럼 글이 아직 없습니다.