AI Medical Compendium Topic

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Rice Blast Disease Recognition Using a Deep Convolutional Neural Network.

Scientific reports
Rice disease recognition is crucial in automated rice disease diagnosis systems. At present, deep convolutional neural network (CNN) is generally considered the state-of-the-art solution in image recognition. In this paper, we propose a novel rice bl...

Fuzzy controller based E-nose classification of Sitophilus oryzae infestation in stored rice grain.

Food chemistry
Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. o...

Deep learning for DNase I hypersensitive sites identification.

BMC genomics
BACKGROUND: The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources availab...

PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network.

PloS one
Rice is a staple food in Asia and it contributes significantly to the Gross Domestic Product (GDP) of Malaysia and other developing countries. Brown Planthopper (BPH) causes high levels of economic loss in Malaysia. Identification of BPH presence and...

A novel nanobody and mimotope based immunoassay for rapid analysis of aflatoxin B1.

Talanta
Mimotopes could replace mycotoxins and their conjugates to develop immunoassay methods. The mimotopes obtained by phage display technology were mainly using monoclonal antibodies or polyclonal antibodies as targets. However, the mimotope of recombina...

A novel method for predicting cadmium concentration in rice grain using genetic algorithm and back-propagation neural network based on soil properties.

Environmental science and pollution research international
Heavy metal pollution is a global ecological safety issue, especially in crops, where it directly threatens regional ecological security and human health. In this study, the back-propagation (BP) neural network optimized by the genetic algorithm (GA)...

Isolation and identification of immunomodulatory selenium-containing peptides from selenium-enriched rice protein hydrolysates.

Food chemistry
The RAW264.7 cell model was employed to screen immunomodulatory selenium-containing peptides from selenium-enriched rice protein hydrolysates (SPHs). Moreover, the selenium-containing peptides of high-activity protein hydrolysates were purified by Se...

MCRiceRepGP: a framework for the identification of genes associated with sexual reproduction in rice.

The Plant journal : for cell and molecular biology
Rice is an important cereal crop, being a staple food for over half of the world's population, and sexual reproduction resulting in grain formation underpins global food security. However, despite considerable research efforts, many of the genes, esp...

Evaluation of multiple linear, neural network and penalised regression models for prediction of rice yield based on weather parameters for west coast of India.

International journal of biometeorology
Rice is generally grown under completely flooded condition and providing food for more than half of the world's population. Any changes in weather parameters might affect the rice productivity thereby impacting the food security of burgeoning populat...

Method for the determination of Pb, Cd, Zn, Mn and Fe in rice samples using carbon nanotubes and cationic complexes of batophenanthroline.

Food chemistry
Among cereals, rice is the second most cultivated staple crop in the world. It may be contaminated by toxic heavy metals present in water or soil. Therefore, monitoring the presence of heavy metals in rice and its products is a matter of a great impo...