Pesticide Residue Coverage Estimation on Citrus Leaf Using Image Analysis Assisted by Machine Learning by Adarsh Basavaraju, Edwin Davidson, Giulio Diracca, Chen Chen, Swadeshmukul Santra

“…As of today, there are no guiding digital tools available for citrus growers to provide pesticide residue leaf coverage analysis after foliar applications. Herein, we are the first to report software assisted by lightweight machine learning (ML) to determine the Kocide 3000 and Oxytetracycline (OTC) residue coverage on citrus leaves based on image data analysis. …”
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Mendelian Randomization Analysis Reveal the Role of Circulating Inflammatory Proteins in Mediating Functional Brain Networks and Peripheral Neuropathic Pain Effects by Wen‐Hui Liu, Hui‐Min Hu, Chen Li, Qing Shi, Yi‐Fan Li, Peng Mao, Bi‐Fa Fan

“…We performed two‐sample MR analysis to investigate the causal effects of functional brain networks on PHN and TN. …”
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Deep Learning-Based Classification of Canine Cataracts from Ocular B-Mode Ultrasound Images by Sanghyeon Park, Seokmin Go, Seonhyo Kim, Jaeho Shim

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A hybrid encryption framework leveraging quantum and classical cryptography for secure transmission of medical images in IoT-based telemedicine networks by Arslan Shafique, Syed Ali Atif Naqvi, Ali Raza, Masoud Ghalaii, Panagiotis Papanastasiou, Julie McCann, Qammer H. Abbasi, Muhammad Ali Imran

“…Abstract In the era of the Internet of Things (IoT), the transmission of medical reports in the form of scan images for collaborative diagnosis is vital for any telemedicine network. …”
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Optimizing Fingerprint Identification: CNNs With Raw Images Versus Handcrafted Features for Real-Time Systems by Shaik Salma, Tauheed Ahmed, Garimella Ramamurthy

“…This study investigates the balance between accuracy and computational efficiency(thereby speed) by comparing two approaches: training a Convolutional Neural Network (CNN) with raw fingerprint images and training a CNN using handcrafted fingerprint features. …”
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Automatic engagement of limbic and prefrontal networks in response to food images reflects distinct information about food hedonics and inhibitory control by Jason A. Avery, Madeline Carrington, John E. Ingeholm, Valerie Darcey, W. Kyle Simmons, Kevin D. Hall, Alex Martin

“…A data-driven clustering approach based on Representational Similarity Analysis partitioned food-responsive brain regions into two sub-networks based on their multivariate response to food pictures: a Prefrontal network composed of fronto-parietal brain regions and a Limbic network composed of cortico-limbic and sub-cortical brain regions. …”
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Construction of an Intelligent Analysis System for Crop Health Status Based on Drone Remote Sensing Data and CNN by Haolin Yang, Peilong Xu, Shengtian Zhang, Hyeonseok Kim, Incheol Shin

“…To address the shortcomings of traditional monitoring methods, which are characterized by high labor intensity, low efficiency, and insufficient timeliness, this paper proposes an innovative intelligent analysis system. The system uses remote sensing data from drones and convolutional neural network technology to achieve efficient crop classification and accurate identification of pests and diseases. …”
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Auto Machine Learning and Convolutional Neural Network in Diabetes Mellitus Research—The Role of Histopathological Images in Designing and Exploring Experimental Models by Iulian Tătaru, Simona Moldovanu, Oana-Maria Dragostin, Carmen Lidia Chiţescu, Alexandra-Simona Zamfir, Ionut Dragostin, Liliana Strat, Carmen Lăcrămioara Zamfir

“…Histopathological images represent a valuable data source for pathologists, who can provide clinicians with essential landmarks for complex pathologies. …”
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An Innovative Artificial Intelligence Classification Model for Non-Ischemic Cardiomyopathy Utilizing Cardiac Biomechanics Derived from Magnetic Resonance Imaging by Liqiang Fu, Peifang Zhang, Liuquan Cheng, Peng Zhi, Jiayu Xu, Xiaolei Liu, Yang Zhang, Ziwen Xu, Kunlun He

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A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data by David M. Morris, Chengjia Wang, Giorgos Papanastasiou, Calum D. Gray, Wei Xu, Samuel Sjöström, Sammy Badr, Julien Paccou, Scott IK Semple, Tom MacGillivray, William P. Cawthorn

“…Objective: To establish deep learning for high-throughput multi-site BMFF analysis from UKBB MRI data. Materials and methods: We studied males and females aged 60–69. …”
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Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography by Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki

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A Two-Stage Method for Diagnosing COVID-19, Leveraging CNN, and Transfer Learning on CT Scan Images by Touba torabipour, Abolfazl Gandomi, Mohammad Ghanimi

“…Subsequently, a CNN neural network is constructed for image detection and categorization in the second stage. …”
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Coordinate Network Mapping of Focal Brain Volume Differences in ADHD Reveals Common Patterns That Lack Specificity: A Systematic Review by Juliana Wall, Gillian N. Miller, Joseph J. Taylor, Jacob L. Stubbs, Simon K. Warfield, Alexander L. Cohen

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Manually classified dataset of leaning and standing personnel images for construction site monitoring and neural network training(Repositorio Institucional – Universidad de Lima) by Alexandre Almeida Del Savio, Ana Luna Torres, Daniel Cárdenas-Salas, Mónica Vergara Olivera, Gianella Urday Ibarra

“…This data paper presents a manually labeled dataset of 1,214 images of personnel captured from a construction site using four static cameras. …”
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Investigating imaging network markers of cognitive dysfunction and pharmacoresistance in newly diagnosed epilepsy: a protocol for an observational cohort study in the UK by Anthony Guy Marson, Marta García-Fiñana, Christophe de Bézenac, Gus Baker, Perry Moore, Nicola Leek, Rajiv Mohanraj, Leonardo Bonilha, Mark Richardson, Simon Keller

“…Patients will be followed up every 6 months for a 24-month period to assess treatment outcomes. Connectivity- and network-based analyses of EEG and MRI data will be carried out and examined in relation to neuropsychological evaluation and patient treatment outcomes. …”
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An enhanced deep learning model for accurate classification of ovarian cancer from histopathological images by Anik Kumar Saha, Muntezar Rabbani, Anika Saba Ibte Sum, M. F. Mridha, Md Mohsin Kabir

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Artificial Neural Networks for Image Processing in Precision Agriculture: A Systematic Literature Review on Mango, Apple, Lemon, and Coffee Crops by Christian Unigarro, Jorge Hernandez, Hector Florez

“…It is based on the collection and analysis of agricultural data to support decision making in agricultural processes. …”
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Deciphering shared molecular dysregulation across Parkinson’s disease variants using a multi-modal network-based data integration and analysis by Alise Zagare, Irina Balaur, Adrien Rougny, Claudia Saraiva, Matthieu Gobin, Anna S. Monzel, Soumyabrata Ghosh, Venkata P. Satagopam, Jens C. Schwamborn

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Development of a model for detection and analysis of inclusions in tomographic images of iron castings using decision trees by Dorota Wilk-Kołodziejczyk, Aleksandra Nowotny, Izabela Krzak, Adam Tchórz, Krzysztof Jaśkowiec, Marcin Małysza, Adam Bitka, Mirosław Głowacki, Marzanna Książek, Łukasz Marcjan

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Uncertainty-Aware Adaptive Multiscale U-Net for Low-Contrast Cardiac Image Segmentation by A. S. M. Sharifuzzaman Sagar, Muhammad Zubair Islam, Jawad Tanveer, Hyung Seok Kim

“…Medical image analysis is critical for diagnosing and planning treatments, particularly in addressing heart disease, a leading cause of mortality worldwide. …”
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