AIMC Topic: Algorithms

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Development of New Diagnostic Techniques - Machine Learning.

Advances in experimental medicine and biology
Traditional diagnoses on addiction reply on the patients' self-reports, which are easy to be dampened by false memory or malingering. Machine learning (ML) is a data-driven procedure that learns algorithms from training data and makes predictions. It...

Decision Support Systems in Health Care - Velocity of Apriori Algorithm.

Studies in health technology and informatics
The amount of stored data in health information systems can reach tera- and petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently use...

Learning Parameter-Advising Sets for Multiple Sequence Alignment.

IEEE/ACM transactions on computational biology and bioinformatics
While the multiple sequence alignment output by an aligner strongly depends on the parameter values used for the alignment scoring function (such as the choice of gap penalties and substitution scores), most users rely on the single default parameter...

An Approach of Non-Linear Systems Through Fuzzy Control Based on Takagi-Sugeno Method.

Advances in experimental medicine and biology
Today, the advanced technology is a part of the everyday's life. As a result, most of the applications used require a more complex system in order to achieve a better performance. These systems have a mathematic background indicating the need of a be...

Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series.

Studies in health technology and informatics
The purpose of this work is to evaluate methods from deep learning for application to Magnetic Resonance Fingerprinting (MRF). MRF is a recently proposed measurement technique for generating quantitative parameter maps. In MRF a non-steady state sign...

Adaptive Sampling Technique Using Regression Modelling and Fuzzy Inference System for Network Traffic.

Studies in health technology and informatics
Electronic-health relies on extensive computer networks to facilitate access and to communicate various types of information in the form of data packets. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due ...

Feedforward Chemical Neural Network: An In Silico Chemical System That Learns xor.

Artificial life
Inspired by natural biochemicals that perform complex information processing within living cells, we design and simulate a chemically implemented feedforward neural network, which learns by a novel chemical-reaction-based analogue of backpropagation....

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

Sao Paulo medical journal = Revista paulista de medicina
CONTEXT AND OBJECTIVE:: Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnos...

A neural network - based algorithm for predicting stone - free status after ESWL therapy.

International braz j urol : official journal of the Brazilian Society of Urology
OBJECTIVE: The prototype artificial neural network (ANN) model was developed using data from patients with renal stone, in order to predict stone-free status and to help in planning treatment with Extracorporeal Shock Wave Lithotripsy (ESWL) for kidn...

Comparison of Grouping Methods for Template Extraction from VA Medical Record Text.

Studies in health technology and informatics
We investigate options for grouping templates for the purpose of template identification and extraction from electronic medical records. We sampled a corpus of 1000 documents originating from Veterans Health Administration (VA) electronic medical rec...