Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …

Multi-instance (MI) learning is a variant of inductive machine learning, where each learning
example contains a bag of instances instead of a single feature vector. The term commonly …

Multiple instance learning (MIL) is a variation of supervised learning where a single class
label is assigned to a bag of instances. In this paper, we state the MIL problem as learning …

Of late, neural networks and Multiple Instance Learning (MIL) are both attractive topics in the
research areas related to Artificial Intelligence. Deep neural networks have achieved great …

We introduce a new computer aided detection and diagnosis system for lung cancer
screening with low-dose CT scans that produces meaningful probability assessments. Our …

The recent development in learning deep representations has demonstrated its wide
applications in traditional vision tasks like classification and detection. However, there has …

Witten and Frank's textbook was one of two books that 1 used for a data mining class in the
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …

This paper presents two new formulations of multiple-instance learning as a maximum
margin problem. The proposed extensions of the Support Vector Machine (SVM) learning …

Data Mining Page 1 Data Mining Practical Machine Learning Tools and Techniques Third
Edition Ian H. Witten Eibe Frank Mark A. Hall ELSEVIER AMSTERDAM • BOSTON • …

Motivation: High-content screening (HCS) technologies have enabled large scale imaging
experiments for studying cell biology and for drug screening. These systems produce …