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A novel hybrid model to predict concomitant diseases for Hashimoto’s thyroiditis
Hashimoto’s thyroiditis is an autoimmune disorder characterized by the destruction of thyroid cells through immune-mediated mechanisms involving...
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A hybrid Stacking-SMOTE model for optimizing the prediction of autistic genes
PurposeAutism spectrum disorder(ASD) is a disease associated with the neurodevelopment of the brain. The autism spectrum can be observed in early...
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Hybrid AI model for estimating the canopy photosynthesis of eggplants
Modern models for estimating canopy photosynthetic rates ( A c ) can be broadly classified into two categories, namely, process-based mechanistic models...
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NmTHC: a hybrid error correction method based on a generative neural machine translation model with transfer learning
BackgroundsThe single-pass long reads generated by third-generation sequencing technology exhibit a higher error rate. However, the circular...
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Time series-based hybrid ensemble learning model with multivariate multidimensional feature coding for DNA methylation prediction
BackgroundDNA methylation is a form of epigenetic modification that impacts gene expression without modifying the DNA sequence, thereby exerting...
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Protein–protein interaction site prediction by model ensembling with hybrid feature and self-attention
BackgroundProtein–protein interactions (PPIs) are crucial in various biological functions and cellular processes. Thus, many computational approaches...
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An adaptive multi-modal hybrid model for classifying thyroid nodules by combining ultrasound and infrared thermal images
BackgroundTwo types of non-invasive, radiation-free, and inexpensive imaging technologies that are widely employed in medical applications are...
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An Optimized Hybrid ARIMA-LSTM Model for Time Series Forecasting of Agricultural Production in India
The role of agriculture in a country’s national income is very important. The zero-hunger sustainable goal of the United Nations cannot be achieved...
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HEC-ASD: a hybrid ensemble-based classification model for predicting autism spectrum disorder disease genes
PurposeAutism spectrum disorder (ASD) is the most prevalent disease today. The causes of its infection may be attributed to genetic causes by 80% and...
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Large-scale lexical and genetic alignment supports a hybrid model of Han Chinese demic and cultural diffusions
The Han Chinese history is shaped by substantial demographic activities and sociocultural transmissions. However, it remains challenging to assess...
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Bone Regeneration with 3D-Printed Hybrid Bone Scaffolds in a Canine Radial Bone Defect Model
Background:The repair of large bone defects remains a significant challenge in clinical practice and requires bone grafts or substitute materials. In...
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Lokatt: a hybrid DNA nanopore basecaller with an explicit duration hidden Markov model and a residual LSTM network
BackgroundBasecalling long DNA sequences is a crucial step in nanopore-based DNA sequencing protocols. In recent years, the CTC-RNN model has become...
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A successful hybrid deep learning model aiming at promoter identification
BackgroundThe zone adjacent to a transcription start site (TSS), namely, the promoter, is primarily involved in the process of DNA transcription...
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Hybrid-hybrid correction of errors in long reads with HERO
Although generally superior, hybrid approaches for correcting errors in third-generation sequencing (TGS) reads, using next-generation sequencing...
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Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels
Key messageAn original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and...
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An integrated model to optimize planting density and sufficient irrigation depth for increasing hybrid maize seeds yield
Optimizing planting density and irrigation depth of hybrid maize seed production is important for ensuring food and water security. A higher planting...
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ARIMAX—Artificial neural network hybrid model for predicting semilooper (Chrysodeixis acuta) incidence on soybean
Insect pest and weather relations analysed using statistical models empower crop pest management through their capacity to forewarn abundance or...
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Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance
Key messageSchemes that use genomic prediction outperform others, updating testers increases hybrid genetic gain, and larger population sizes tend to...
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Hybrid origin and hybrid status of the endangered Ilex sanqingshanensis revealed by molecular and morphological evidence
Identification of natural hybrids considered as endangered species is of vital importance in taxonomy and biodiversity conservation, as natural...
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A CNN-LSTM-att hybrid model for classification and evaluation of growth status under drought and heat stress in chinese fir (Cunninghamia lanceolata)
BackgroundCunninghamia lanceolata (Chinese fir), is one of the most important timber trees in China. With the global warming, to develop new...
