AIMC Topic: Algorithms

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Commissioning Monte Carlo algorithm for robotic radiosurgery using cylindrical 3D-array with variable density inserts.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
INTRODUCTION: To commission the Monte Carlo (MC) algorithm based model of CyberKnife robotic stereotactic system (CK) and evaluate the feasibility of patient specific QA using the ArcCHECK cylindrical 3D-array (AC) with Multiplug inserts (MP).

Analysis of the Importance of Oxides and Clays in Cd, Cr, Cu, Ni, Pb and Zn Adsorption and Retention with Regression Trees.

PloS one
This study determines the influence of the different soil components and of the cation-exchange capacity on the adsorption and retention of different heavy metals: cadmium, chromium, copper, nickel, lead and zinc. In order to do so, regression models...

Neural-Network-Biased Genetic Algorithms for Materials Design: Evolutionary Algorithms That Learn.

ACS combinatorial science
Machine learning has the potential to dramatically accelerate high-throughput approaches to materials design, as demonstrated by successes in biomolecular design and hard materials design. However, in the search for new soft materials exhibiting prop...

V-ELMpiRNAPred: Identification of human piRNAs by the voting-based extreme learning machine (V-ELM) with a new hybrid feature.

Journal of bioinformatics and computational biology
Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this p...

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction: a review.

Journal of neural engineering
Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently ...

Advantages of Synthetic Noise and Machine Learning for Analyzing Radioecological Data Sets.

PloS one
The ecological effects of accidental or malicious radioactive contamination are insufficiently understood because of the hazards and difficulties associated with conducting studies in radioactively-polluted areas. Data sets from severely contaminated...

Construction of longitudinal prediction targets using semisupervised learning.

Statistical methods in medical research
In establishing prognostic models, often aided by machine learning methods, much effort is concentrated in identifying good predictors. However, the same level of rigor is often absent in improving the outcome side of the models. In this study, we fo...

Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

Medical image analysis
This paper addresses the problem of classifying materials from microspectroscopy at a pixel level. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels. W...

An expert system for selecting wart treatment method.

Computers in biology and medicine
As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV) and may grow on all parts of body, especially hands and feet. There are several treatment methods for this illness. However, none of them can heal all patients. Cons...

SVM and SVM Ensembles in Breast Cancer Prediction.

PloS one
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among...