AIMC Topic: Deep Learning
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Monochromatic LeafAdaptNet (MLAN): an adaptive approach to spinach leaf disease detection using monochromatic imaging.
World journal of microbiology & biotechnology
Jul 8, 2025
A country's economic growth heavily relies on agricultural productivity, specifically nutrition derived from vegetables and leafy greens. Spinach, abundant in iron, vitamins, and other essential nutrients, plays a vital role in maintaining the health...
Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.
Scientific reports
Jul 8, 2025
Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinates. While traditional approaches include using skin prick tests (SPT) to determine the presence of AR, It is often not related to actual symptoms, and ...
Plant attribute extraction: An enhancing three-stage deep learning model for relational triple extraction.
PloS one
Jul 8, 2025
Various plant attributes, such as growing environment, growth cycle, and ecological distribution, can provide support to fields like agricultural production and biodiversity. This information is widely dispersed in texts. Manual extraction of this in...
Harnessing deep learning for fusion-based heavy metal contamination index prediction in groundwater.
Journal of contaminant hydrology
Jul 7, 2025
Groundwater contamination by heavy metals presents a major environmental threat with serious implications for public health and resource sustainability. This study proposes a novel deep learning-based data fusion framework to predict heavy metal cont...
Predicting the Effects of Charge Mutations on the Second Osmotic Virial Coefficient for Therapeutic Antibodies via Coarse-Grained Molecular Simulations and Deep Learning Methods.
Molecular pharmaceutics
Jul 7, 2025
The impact of various charge mutations on the second osmotic virial coefficient was examined for three model therapeutic monoclonal antibodies (MAbs) at representative formulation pH values by using coarse-grained (CG) molecular modeling. The wild-ty...
Hippocampal blood oxygenation predicts choices about everyday consumer experiences: A deep-learning approach.
Proceedings of the National Academy of Sciences of the United States of America
Jul 7, 2025
This research investigates the neurophysiological mechanisms of experiential versus monetary choices under risk. While ventral striatum and insula activity are instrumental in predicting monetary choices, we find that hippocampal activity plays a key...
Deep learning method for cucumber disease detection in complex environments for new agricultural productivity.
BMC plant biology
Jul 7, 2025
Cucumber disease detection under complex agricultural conditions faces significant challenges due to multi-scale variation, background clutter, and hardware limitations. This study proposes YOLO-Cucumber, an improved lightweight detection algorithm b...
Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jul 7, 2025
OBJECTIVES: The purpose of this study is to mainly develop a predictive model based on clinicoradiological and radiomics features from preoperative gadobenate-enhanced (Gd-BOPTA) magnetic resonance imaging (MRI) using multilayer perceptron (MLP) deep...
Gender difference in cross-sectional area and fat infiltration of thigh muscles in the elderly population on MRI: an AI-based analysis.
European radiology experimental
Jul 7, 2025
BACKGROUND: Aging alters musculoskeletal structure and function, affecting muscle mass, composition, and strength, increasing the risk of falls and loss of independence in older adults. This study assessed cross-sectional area (CSA) and fat infiltrat...
Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study.
Scientific reports
Jul 7, 2025
The videofluoroscopic swallowing study (VFSS) is the gold standard for diagnosing dysphagia, but its interpretation is time-consuming and requires expertise. This study developed a deep learning model for automatically detecting penetration and aspir...
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