Testing of Six Different AI-Based Models: A Deep Dive to Improve Cervical Cancer Screening

The goal of the Kaggle* Competition sponsored by Intel and MobileODT* was to use artificial intelligence to improve the precision and accuracy of cervical cancer screening. This case study follows the process used by the third-place winning team, GRXJ. They pooled their respective skill sets to create an algorithm that would improve this life-saving diagnostic procedure.
作者: 管理 最后更新时间: 2019/02/21 - 11:16

Brain Tumor Segmentation using Fully Convolutional Tiramisu Deep Learning Architecture

The aim of the work was to implement, train and evaluate the quality of automated brain tumor multi-label segmentation technique for Magnetic Resonance Imaging based on Tiramisu deep learning architecture.
作者: Kocot, Szymon 最后更新时间: 2019/03/26 - 16:20

Using Artificial Intelligence Solutions to Improve Patient Care

The University of California, San Francisco targets data-fueled insights for clinical medicine with Intel® Xeon® processors.

作者: 管理 最后更新时间: 2018/10/19 - 10:12

Case Study: Optimized Code for Neural Cell Simulations

One of the Intel® Modern Code Developer Challenge winners, Daniel Falguera, describes many of the optimizations he implemented and why some didn't work.
作者: 最后更新时间: 2019/10/03 - 07:55

New Levels of CT Image Performance and New Levels in Radiation Dose Management

Veo, GE Healthcare's new CT Scanner reconstruction technology, provides high resolution CT images allowing radiologists to maximize diagnostic accuracy at an optimized low dose to the patient. This paper describes the MBIR optimization steps taken.
作者: 最后更新时间: 2019/10/15 - 17:00