Results 211 to 220 of about 79,319 (254)

A Review on Image Processing and Fractal Analysis in Oral Potentially Malignant Disorders

Oral Diseases, EarlyView.
ABSTRACT Aim The clinical evaluation of patients with oral potentially malignant disorders is primarily based on physical examination and observable clinical features. Clinical photographs play a key role in patient monitoring and help identify signs that may indicate malignant transformation.
André Goulart Poletto, Flaviana Silva de Souza, Lilian Bezerra, Thiago Pires Claudio, Jesse Parente Tocantins, Helena Miguel Cotter, Riéli Elis Schulz, Karin Berria Tomazelli, Elena Riet Correa Rivero, Fabio Luiz Coracin, Gustavo Davi Rabelo   +10 more
wiley   +1 more source

Machine Learning‐Driven Construction of High‐Yielding Cucumber Plant Architectures in Greenhouse Environments

Plant Biotechnology Journal, EarlyView.
Schematic summary of the machine learning‐driven analysis for high‐yield cucumber architecture. This study employs machine learning methods to analyze key shoot and root traits, building a predictive model for yield. The analysis identifies an optimal plant architecture: a compact and sturdy shoot structure, combined with a narrow yet larger‐diameter ...
Cuifang Zhu, Hongjun Yu, Caili Zhao, Hongyang Wu, Xiaoyang Wan, Tao Lu, Yang Li, Weijie Jiang, Qiang Li   +8 more
wiley   +1 more source

PlantCTCIP: Chromatin Interaction Prediction Using Convolutional Neural Network and Transformer in Plants

Plant Biotechnology Journal, EarlyView.
ABSTRACT Chromatin interactions establish spatial proximity between distant regulatory elements and their target genes, significantly influencing gene expression, and phenotypic traits. In this study, we present a plant chromatin interaction prediction model called PlantCTCIP based on Convolutional Neural Networks and Transformer.
Zhenye Wang, Siyu Zhou, Ze Guo, Zilan Ning, Jiaqi Cai, Ran Zhao, Ao Xie, Quan Li, Jiangling Zhang, Yongsheng Zhao, Peizhang Li, Haiping Si, Jianbing Yan, Yong Peng, Jianxiao Liu   +14 more
wiley   +1 more source

DNAwhisper: An Integrated Deep Learning Pyramidal Framework for Multi‐Trait Genomic Prediction and Adaptive Marker Prioritisation

Plant Biotechnology Journal, EarlyView.
ABSTRACT Genomic selection (GS) is critical for accelerating genetic gain in modern plant breeding. Deep learning approaches offer powerful non‐linear representation capabilities for modelling non‐additive effects. However, their application in GS remains restricted, as high‐dimensional, low‐sample and noisy data hinder the identification of ...
Yuexin Ma, Xiang Li, Xiaohao Ji, Chunying Wang, Di Zhang, Tingting Zhai, Haibo Wang, Ping Liu   +7 more
wiley   +1 more source

A High‐Throughput Phenotyping Pipeline for Quinoa (Chenopodium quinoa) Panicles Using Image Analysis With Convolutional Neural Networks

Plant Breeding, EarlyView.
ABSTRACT Quinoa is a grain crop with excellent nutritional properties that has attracted global attention for its potential contribution to future food security in a changing climate. Despite its long history of cultivation, quinoa has been improved little by modern breeding and is a niche crop outside its native cultivation area.
Flavio Lozano‐Isla, Lydia Kienbaum, Bettina I. G. Haussmann, Karl Schmid   +3 more
wiley   +1 more source

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype‐to‐phenotype relationships is generally lacking.
John G. Hodge, Andrew D. B. Leakey
wiley   +1 more source

Assessing forest fragmentation and biodiversity impacts in sub‐Saharan Africa: Methodological challenges and conservation strategies for small‐scale agricultural landscapes

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Tropical forests in sub‐Saharan Africa (SSA) harbor around one‐third of the world's species but are becoming more fragmented due to the expansion of human settlements and small‐scale agricultural (SCA) areas. This study systematically reviewed the approaches and methods used to analyze forest fragmentation and its impact on biodiversity in SSA,
Gillie Cheelo, Hastings Shamaoma, Charles Bwalya Chisanga, Jules Christian Zekeng, Stephen Syampungani   +4 more
wiley   +1 more source

Diffusion model‐regularized implicit neural representation for computed tomography metal artifact reduction

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Computed tomography (CT) images are often severely corrupted by artifacts in the presence of metals. Existing supervised metal artifact reduction (MAR) approaches suffer from performance instability on known data due to their reliance on limited paired metal‐clean data, which limits their clinical applicability. Moreover, existing unsupervised
Jie Wen, Chenhe Du, Xiao Wang, Yuyao Zhang   +3 more
wiley   +1 more source