With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Supervised learning and pattern recognition is a crucial area of research in information
retrieval, knowledge engineering, image processing, medical imaging, and intrusion …

Background An appropriate sample size is essential for obtaining a precise and reliable
outcome of a study. In machine learning (ML), studies with inadequate samples suffer from …

Many real-world systems can be studied in terms of pattern recognition tasks, so that proper
use (and understanding) of machine learning methods in practical applications becomes …

Automatic keyword extraction is an important research direction in text mining, natural
language processing and information retrieval. Keyword extraction enables us to represent …

Purpose To improve the detection of corneal ectasia susceptibility using tomographic data.
Design Multicenter case-control study. Methods Data from patients from 5 different clinics …

Ki67 expression has been a valuable prognostic variable in breast cancer, but has not seen
broad adoption due to lack of standardization between institutions. Automation could …

Software developers require effective effort estimation models to facilitate project planning.
Although Usman et al. systematically reviewed and synthesized the effort estimation models …

Currently, most of the adopted myoelectric schemes for upper limb prostheses do not
provide users with intuitive control. Higher accuracies have been reported using different …

This paper presents a framework based on machine learning algorithms to predict nutrient
content in leaf hyperspectral measurements. This is the first approach to evaluate macro-and …