Pinned Repositories
BreastCancerPrediction
Breast cancer has the second highest mortality rate in women next to lung cancer. As per clinical statistics, 1 in every 8 women is diagnosed with breast cancer in their lifetime. However, periodic clinical check-ups and self-tests help in early detection and thereby significantly increase the chances of survival. Invasive detection techniques cause rupture of the tumor, accelerating the spread of cancer to adjoining areas. Hence, there arises the need for a more robust, fast, accurate, and efficient non-invasive cancer detection system. Early detection can give patients more treatment options. In order to detect signs of cancer, breast tissue from biopsies is stained to enhance the nuclei and cytoplasm for microscopic examination. Then, pathologists evaluate the extent of any abnormal structural variation to determine whether there are tumors. Architectural Distortion (AD) is a very subtle contraction of the breast tissue and may represent the earliest sign of cancer. Since it is very likely to be unnoticed by radiologists, several approaches have been proposed over the years but none using deep learning techniques. AI will become a transformational force in healthcare and soon, computer vision models will be able to get a higher accuracy when researchers have the access to more medical imaging datasets. The application of machine learning models for prediction and prognosis of disease development has become an irrevocable part of cancer studies aimed at improving the subsequent therapy and management of patients. The application of machine learning models for accurate prediction of survival time in breast cancer on the basis of clinical data is the main objective. We have developed a computer vision model to detect breast cancer in histopathological images. Two classes will be used in this project: Benign and Malignant
dooringx
快速高效搭建可视化拖拽平台
md2docx
Markdown to Word docx file conversion windows
My-Blog-layui
layui 版本的 My-Blog : A simple & beautiful blogging system implemented with spring-boot & layui & thymeleaf & mybatis My Blog 是由 SpringBoot + Layui + Mybatis + Thymeleaf 等技术实现的 Java 博客系统，页面美观、功能齐全、部署简单及完善的代码，一定会给使用者无与伦比的体验
OneFile
只有一个文件！
visoscope20D
visoScope designed for 20D PMMA oDocs lens
visoscope30D
visoScope
runmanfm's Repositories
runmanfm/BreastCancerPrediction
Breast cancer has the second highest mortality rate in women next to lung cancer. As per clinical statistics, 1 in every 8 women is diagnosed with breast cancer in their lifetime. However, periodic clinical check-ups and self-tests help in early detection and thereby significantly increase the chances of survival. Invasive detection techniques cause rupture of the tumor, accelerating the spread of cancer to adjoining areas. Hence, there arises the need for a more robust, fast, accurate, and efficient non-invasive cancer detection system. Early detection can give patients more treatment options. In order to detect signs of cancer, breast tissue from biopsies is stained to enhance the nuclei and cytoplasm for microscopic examination. Then, pathologists evaluate the extent of any abnormal structural variation to determine whether there are tumors. Architectural Distortion (AD) is a very subtle contraction of the breast tissue and may represent the earliest sign of cancer. Since it is very likely to be unnoticed by radiologists, several approaches have been proposed over the years but none using deep learning techniques. AI will become a transformational force in healthcare and soon, computer vision models will be able to get a higher accuracy when researchers have the access to more medical imaging datasets. The application of machine learning models for prediction and prognosis of disease development has become an irrevocable part of cancer studies aimed at improving the subsequent therapy and management of patients. The application of machine learning models for accurate prediction of survival time in breast cancer on the basis of clinical data is the main objective. We have developed a computer vision model to detect breast cancer in histopathological images. Two classes will be used in this project: Benign and Malignant
runmanfm/dooringx
快速高效搭建可视化拖拽平台
runmanfm/md2docx
Markdown to Word docx file conversion windows
runmanfm/My-Blog-layui
layui 版本的 My-Blog : A simple & beautiful blogging system implemented with spring-boot & layui & thymeleaf & mybatis My Blog 是由 SpringBoot + Layui + Mybatis + Thymeleaf 等技术实现的 Java 博客系统，页面美观、功能齐全、部署简单及完善的代码，一定会给使用者无与伦比的体验
runmanfm/OneFile
只有一个文件！
runmanfm/visoscope20D
visoScope designed for 20D PMMA oDocs lens
runmanfm/visoscope30D
visoScope