AIMC Topic: Algorithms

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An expert system design to diagnose cancer by using a new method reduced rule base.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controll...

Evaluation of a Machine Learning-Based Prognostic Model for Unrelated Hematopoietic Cell Transplantation Donor Selection.

Biology of blood and marrow transplantation : journal of the American Society for Blood and Marrow Transplantation
The survival of patients undergoing hematopoietic cell transplantation (HCT) from unrelated donors for acute leukemia exhibits considerable variation, even after stringent genetic matching. To improve the donor selection process, we attempted to crea...

Accelerated low-rank representation for subspace clustering and semi-supervised classification on large-scale data.

Neural networks : the official journal of the International Neural Network Society
The scalability of low-rank representation (LRR) to large-scale data is still a major research issue, because it is extremely time-consuming to solve singular value decomposition (SVD) in each optimization iteration especially for large matrices. Sev...

GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

Neural networks : the official journal of the International Neural Network Society
Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumula...

Merging weighted SVMs for parallel incremental learning.

Neural networks : the official journal of the International Neural Network Society
Parallel incremental learning is an effective approach for rapidly processing large scale data streams, where parallel and incremental learning are often treated as two separate problems and solved one after another. Incremental learning can be imple...

Self-organization in aggregating robot swarms: A DW-KNN topological approach.

Bio Systems
In certain swarm applications, where the inter-agent distance is not the only factor in the collective behaviours of the swarm, additional properties such as density could have a crucial effect. In this paper, we propose applying a Distance-Weighted ...

A novel selection method of seismic attributes based on gray relational degree and support vector machine.

PloS one
The selection of seismic attributes is a key process in reservoir prediction because the prediction accuracy relies on the reliability and credibility of the seismic attributes. However, effective selection method for useful seismic attributes is sti...

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Medical image analysis
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, as a small, soft, and flexible abdominal organ, the pancreas demonstrates very high inter-patient a...