Search Results for author:
Found 7 papers, 2 papers with code
Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review
Cancer remains one of the most challenging diseases to treat in the medical field.
Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm
The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA, and PTEN) based on features extracted from the corresponding region of five MRI contrast images.
A Novel Hybrid Ordinal Learning Model with Health Care Application
This situation is quite common in health care datasets due to limitations of the diagnostic instrument, sparse clinical visits, or/and patient dropout.
Translated Skip Connections -- Expanding the Receptive Fields of Fully Convolutional Neural Networks
The effective receptive field of a fully convolutional neural network is an important consideration when designing an architecture, as it defines the portion of the input visible to each convolutional kernel.
Multi-Modal Recommendation System with Auxiliary Information
Context-aware recommendation systems improve upon classical recommender systems by including, in the modelling, a user's behaviour.
Dictionary learning for clustering on hyperspectral images
Dictionary learning and sparse coding have been widely studied as mechanisms for unsupervised feature learning.
Improved Image Coding Autoencoder With Deep Learning
In this paper, we build autoencoder based pipelines for extreme end-to-end image compression based on Ball\'e's approach, which is the state-of-the-art open source implementation in image compression using deep learning.
