AI Medical Compendium Topic:
Data Mining

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Developing a knowledge base to support the annotation of ultrasound images of ectopic pregnancy.

Journal of biomedical semantics
BACKGROUND: Ectopic pregnancy is a frequent early complication of pregnancy associated with significant rates of morbidly and mortality. The positive diagnosis of this condition is established through transvaginal ultrasound scanning. The timing of d...

Comprehensible knowledge model creation for cancer treatment decision making.

Computers in biology and medicine
BACKGROUND: A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and...

Geographical traceability of wild Boletus edulis based on data fusion of FT-MIR and ICP-AES coupled with data mining methods (SVM).

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this work, the data fusion strategy of Fourier transform mid infrared (FT-MIR) spectroscopy and inductively coupled plasma-atomic emission spectrometry (ICP-AES) was used in combination with Support Vector Machine (SVM) to determine the geographic...

Self-Taught convolutional neural networks for short text clustering.

Neural networks : the official journal of the International Neural Network Society
Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC), which can flexibly and successfully inc...

Automatic query generation using word embeddings for retrieving passages describing experimental methods.

Database : the journal of biological databases and curation
Information regarding the physical interactions among proteins is crucial, since protein-protein interactions (PPIs) are central for many biological processes. The experimental techniques used to verify PPIs are vital for characterizing and assessing...

A L1-regularized feature selection method for local dimension reduction on microarray data.

Computational biology and chemistry
Dimension reduction is a crucial technique in machine learning and data mining, which is widely used in areas of medicine, bioinformatics and genetics. In this paper, we propose a two-stage local dimension reduction approach for classification on mic...

An unsupervised machine learning model for discovering latent infectious diseases using social media data.

Journal of biomedical informatics
INTRODUCTION: The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a commu...

Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm.

Computational intelligence and neuroscience
Symbiotic organisms search (SOS) is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a chal...

A "Tuned" Mask Learnt Approach Based on Gravitational Search Algorithm.

Computational intelligence and neuroscience
Texture image classification is an important topic in many applications in machine vision and image analysis. Texture feature extracted from the original texture image by using "Tuned" mask is one of the simplest and most effective methods. However, ...

Multichannel Convolutional Neural Network for Biological Relation Extraction.

BioMed research international
The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are suscep...