Results 201 to 210 of about 1,405,484 (345)

Recent advances in plant disease detection: challenges and opportunities. [PDF]

Plant Methods
Shafay M, Hassan T, Owais M, Hussain I, Khawaja SG, Seneviratne L, Werghi N.   +6 more
europepmc   +1 more source

Comparative Analysis of CNN-Based Deep Learning Architectures for Automatic Plant Disease Classification

Sedat Örenç, Emrullah Acar, Mehmet Siraç Özerdem   +2 more
openalex   +2 more sources

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

IoT-Integrated robotic system for automated plant disease detection and environmental monitoring. [PDF]

Sci Rep
Talaat FM, Ibrahim MA, Karim AA, Elsonbaty HK, Al-Zoghby AM.   +4 more
europepmc   +1 more source

Stability and Hopf bifurcation analysis of a delayed eco-epidemiological model of IYSV disease dynamics in onion plants with nonlinear saturated incidence and logistic growth

, 2022

openalex   +1 more source

Colorectal cancer‐derived FGF19 is a metabolically active serum biomarker that exerts enteroendocrine effects on mouse liver

Molecular Oncology, EarlyView.
Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley, Michael W. Rohr, Joseph A. Goode, Sai Preethi Nakkina, Jignesh G. Parikh, Deborah A. Altomare   +5 more
wiley   +1 more source

Retraction Note: Plant disease recognition using residual convolutional enlightened Swin transformer networks. [PDF]

Sci Rep
Kalpana P, Anandan R, Hussien AG, Migdady H, Abualigah L.   +4 more
europepmc   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

Molecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns, Jaclyn S. Long, Sergio Lilla, Kelly Hodge, Marcus J. G. W. Ladds, Colin Nixon, Paula Fernández‐Palanca, Sara Zanivan, Pilar Acedo, Stephen P. Pereira, Kevin M. Ryan   +10 more
wiley   +1 more source

A hybrid deep learning framework using convolutional and transformer models for robust plant disease classification. [PDF]

Sci Rep
Jawed MM, Tufail FA, Ahmed MZ, R AS, Nallusamy P, Raja KT.   +5 more
europepmc   +1 more source

Plant Diseases [PDF]

Agronomy Journal, 1953
openaire   +2 more sources