Immunophenotype-guided interpretable radiomics model for predicting neoadjuvant anti-PD-1 response in stage III–IV d-MMR/MSI-H colorectal cancer by Xuan Zhang, Zhenhui Li, Yiwen Zhang, Yanli Li, Xi Zhong, Wenjing Jiang, Xiaobo Chen, Zaiyi Liu, Liebin Huang, Caixia Zhang, Lizhu Liu, Ruimin You, Xiaoping Yi

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Construction of a sugar and acid content estimation model for Miliang-1 kiwifruit during storage by LIU Li, YANG Tianyi, DONG Congying, SHI Caiyun, SI Peng, WEI Zhifeng, GAO Dengtao

“…During the research, a hyperspectral imaging system was used to collect hyperspectral reflectance data of these kiwifruits at different storage times. …”
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An artificial intelligence approach to palaeogeographic studies: a case study of the Late Ordovician brachiopods of Laurentia by Akbar Sohrabi

“…Based on the training algorithm and after 146 periods, the training error decreased, but the validation error increased (Fig. 7). …”
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Integrating Gut Microbiome and Metabolomics with Magnetic Resonance Enterography to Advance Bowel Damage Prediction in Crohn’s Disease by Huang L, Meng J, Lin S, Peng Z, Zhang R, Shen X, Zheng W, Zheng Q, Wu L, Wang X, Wang Y, Mao R, Sun C, Li X, Feng ST

“…We combined the three methods into a single comprehensive test.Imaging: Magnetic resonance enterography (MRE), a noninvasive scan, was used to capture clear images of the bowel. …”
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Research status and progress on key technologies of intelligent orchard by CUI Hongwei, LU Xiaoxuan, YANG Yaqing, LU Xinyi, MA Hao, JI Jiangtao, JIN Xin, LI Xiuzhen, ZHAO Zimeng, ZENG Ningning

“…Crop perception technology monitors the health, growth, and pest infestation status of trees using hyperspectral imaging, infrared technology, and other advanced sensors. …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…A comprehensive understanding of a deposit necessitates a series of processing and modeling operations (Hassani Pak, 2000). …”
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3D vector field-guided toolpathing for 3D bioprinting by Meghan Rochelle Griffin, Spencer E. Bertram, Noah P. Robison, Angela Panoskaltsis-Mortari, Ravi Janardan, Michael C. McAlpine

“…It is anticipated that NAATIV3 is generalizable beyond the cardiac application demonstrated here. Directional imaging data from a variety of organs, disease states, and developmental timepoints may be processible by NAATIV3, enabling the creation of models for understanding development, physiology, and pathophysiology. …”
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Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies by Rahul Kumar, Ethan Waisberg, Joshua Ong, Phani Paladugu, Dylan Amiri, Jeremy Saintyl, Jahnavi Yelamanchi, Robert Nahouraii, Ram Jagadeesan, Alireza Tavakkoli

“…Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. …”
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Modern echocardiographic criteria for heart failure with preserved ejection fraction: not only diastolic dysfunction by O. M. Drapkina, O. N. Dzhioeva

“…The most affordable and cost-effective imaging method for the CHpEF diagnosis is transthoracic echocardiography. …”
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Artificial Intelligence: The Latest Advances in the Diagnosis of Bladder Cancer by Satyendra Singh, Ram Mohan Shukla

“…This review explores the current state and potential of AI technologies, including machine learning algorithms, deep learning networks, and computer vision, in enhancing the diagnostic process for bladder cancer. …”
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A machine learning approach to population pharmacokinetic modelling automation by Sam Richardson, Itziar Irurzun Arana, Andrzej Nowojewski, Diansong Zhou, Jacob Leander, Weifeng Tang, Richard Dearden, Megan Gibbs

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SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation by Brandon Theodorou, Anant Dadu, Mike Nalls, Faraz Faghri, Jimeng Sun

“…These models are computer algorithms that simulate how information changes. SECONDGRAM addresses data scarcity by generating realistic follow-up MRI imaging features, thereby enriching limited datasets. …”
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A systematic review of machine learning-based remote sensing data analysis for geological and mined materials characterisation by Sureka Thiruchittampalam, Bikram Pratap Banerjee, Nancy F Glenn, Simit Raval

“…As the volume and complexity of data generated by advanced imaging methods continue to increase, traditional analytical techniques struggle to effectively process and interpret this information. …”
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SCREENING FOR OVARIAN CANCER: REALITY AND PROSPECTS. REVIEW OF THE LITERATURE by E. V. Gerfanova, L. A. Ashrafyan, I. B. Antonova, O. I. Aleshikova, S. V. Ivashina

“…In light of this the need becomes evident for combination of tumor markers with radiological method of imaging, such as transvaginal sonography as the most affordable, safe and multi-reproducible method enabling to most accurately determine the nature of the process, its nosology belonging, as well as to carry out the required dynamic monitoring within a short time. …”
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Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours by Haoran Wang, Peter T. Brown, Jessica Ullom, Douglas P. Shepherd, Rainer Heintzmann, Benedict Diederich

“…Abstract In biological imaging, there is a demand for cost-effective, high-resolution techniques to study dynamic intracellular processes. …”
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Study on Rapid Inversion Method for Chlorophyll Content in Ginseng Leaves Based on Reflectance Spectroscopy by Jinyu Wang, Jin Yang, Jiaqi Chen, Shulong Feng, Zitong Zhao, Mingjia Wang, Nan Song, Wei Zhang, Ci Sun

“…To address the problem that the existing means of detecting chlorophyll in ginseng leaves are time-consuming and disruptive and cannot meet the demand for rapid detection of chlorophyll in ginseng leaves, this study firstly establishes a variety of prediction models for chlorophyll in ginseng leaves based on the hyperspectral reflectance data and the vegetation index, respectively, and determines the strengths and weaknesses of the models by comparing the RMSE and the MAE of the test sets; Secondly, the analytical model construction process used for ginseng leaf chlorophyll content prediction was obtained through comparison and summary, and a fast and non-destructive ginseng leaf chlorophyll prediction method based on hyperspectral imaging technology and combining vegetation indices with machine learning algorithms was proposed; The experimental results showed that the final VI-SPA-RFR ginseng leaf chlorophyll prediction model had the best prediction performance, which had an RMSE of 1.1568 and an MAE of 0.9936 in the test set. …”
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Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding by Xiaomei Hu, Fanqi Liang, Man Zheng, Juying Xie, Shanxi Wang

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Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods by Panagiota-Kyriaki Revelou, Efstathia Tsakali, Anthimia Batrinou, Irini F. Strati

“…The present review provides an overview of ML, feature extraction, and selection algorithms employed for food safety. Several non-destructive techniques are presented, including spectroscopic methods, smartphone-based sensors, paper chromogenic arrays, machine vision, and hyperspectral imaging combined with ML algorithms. …”
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Tympanosclerosis Presenting as Mass: Workup and Differential by Jonnae Y. Barry, Saranya Reghunathan, Abraham Jacob

“…Through imaging and biopsy the diagnosis of tympanosclerosis was made. …”
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Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach. by Daniel U Campos-Delgado, Omar Gutierrez-Navarro, Ricardo Salinas-Martinez, Elvis Duran, Aldo R Mejia-Rodriguez, Miguel J Velazquez-Duran, Javier A Jo

“…The deconvolution process is a key step for quantitative evaluation of fluorescence lifetime imaging microscopy (FLIM) samples. …”
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