Multi-Spectral Optimization for Tissue Probing Using Machine Learning by Yarden Tzabari Kelman, Hadas Lupa Yitzhak, Nadav Shabairou, Shahaf Finder, Zeev Zalevsky

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Deep learning in gastric tissue diseases: a systematic review by Wanderson Gonçalves e Gonçalves, Marcelo Henrique de Paula dos Santos, Fábio Manoel França Lobato, Ândrea Ribeiro-dos-Santos, Gilderlanio Santana de Araújo

“…Despite the emergence of deep learning research on gastric tissues diseases, few intensive reviews are addressing this topic.Method We performed a systematic review related to applications of deep learning in gastric tissue disease analysis by digital histology, endoscopy and radiology images.Conclusions This review highlighted the high potential and shortcomings in deep learning research studies applied to gastric cancer, ulcer, gastritis and non-malignant diseases. …”
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Machine learning reveals distinct gene expression signatures across tissue states in stony coral tissue loss disease by Kelsey M. Beavers, Daniela Gutierrez-Andrade, Emily W. Van Buren, Madison A. Emery, Marilyn E. Brandt, Amy Apprill, Laura D. Mydlarz

Subjects: “…stony coral tissue loss disease…”
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Expression‐based machine learning models for predicting plant tissue identity by Sourabh Palande, Jeremy Arsenault, Patricia Basurto‐Lozada, Andrew Bleich, Brianna N. I. Brown, Sophia F. Buysse, Noelle A. Connors, Sikta Das Adhikari, Kara C. Dobson, Francisco Xavier Guerra‐Castillo, Maria F. Guerrero‐Carrillo, Sophia Harlow, Héctor Herrera‐Orozco, Asia T. Hightower, Paulo Izquierdo, MacKenzie Jacobs, Nicholas A. Johnson, Wendy Leuenberger, Alessandro Lopez‐Hernandez, Alicia Luckie‐Duque, Camila Martínez‐Avila, Eddy J. Mendoza‐Galindo, David Cruz Plancarte, Jenny M. Schuster, Harry Shomer, Sidney C. Sitar, Anne K. Steensma, Joanne Elise Thomson, Damián Villaseñor‐Amador, Robin Waterman, Brandon M. Webster, Madison Whyte, Sofía Zorilla‐Azcué, Beronda L. Montgomery, Aman Y. Husbands, Arjun Krishnan, Sarah Percival, Elizabeth Munch, Robert VanBuren, Daniel H. Chitwood, Alejandra Rougon‐Cardoso

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Deep learning-assisted terahertz intelligent detection and identification of cancer tissue by Xingyu Wang, Yafei Xu, Rong Wang, Nuoman Tian, Zhengpeng Zhu, Shuting Fan, Liuyang Zhang, Ruqiang Yan, Xuefeng Chen

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Intuition-guided Reinforcement Learning for Soft Tissue Manipulation with Unknown Constraints by Xian He, Shuai Zhang, Jian Chu, Tongyu Jia, Lantao Yu, Bo Ouyang

“…The constraints were assumed to be constant during the operation, and there were no obstacles around the soft tissue. To address these problems, an intuition-guided deep reinforcement learning framework based on soft actor-critic (ID-SAC) was proposed for soft tissue manipulation under unknown constraints. …”
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Application of machine learning in depression risk prediction for connective tissue diseases by Leilei Yang, Yuzhan Jin, Wei Lu, Xiaoqin Wang, Yuqing Yan, Yulan Tong, Dinglei Su, Kaizong Huang, Jianjun Zou

Subjects: “…Connective tissue disease…”
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Tracheal Allotransplantation–Lessons Learned by Subramania Iyer, Narayana Subramaniam, Sivakumar Vidhyadharan, Krishnakumar Thankappan, Deepak Balasubramanian, Balasubramanian K. R., Arun Nair, Kishore Purushottaman, Janarthanan Ramu, Zachariah Paul

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IMPROVING STUDENT'S COGNITIVE LEARNING OUTCOME THROUGH DISCOVERY LEARNING MODEL IN STRUCTURE AND FUNCTION OF PLANT TISSUES SUBJECT by Nurhayati Dukomalamo, Bahtiar Bahtiar, Arini Zahrotun N

“…The research result indicates that the application of discovery learning model could improve the cognitive learning outcome and learning activities among students at class VIII-4 of SMP Negeri 4 Kota Ternate in the subject of the Structure and Function of Plant Tissues.…”
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Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning by Alfredo Ordinola, David Abramian, Magnus Herberthson, Anders Eklund, Evren Özarslan

“…Abstract Diffusion magnetic resonance imaging (diffusion MRI) is widely employed to probe the diffusive motion of water molecules within the tissue. Numerous diseases and processes affecting the central nervous system can be detected and monitored via diffusion MRI thanks to its sensitivity to microstructural alterations in tissue. …”
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Deep Learning in Spinal Endoscopy: U-Net Models for Neural Tissue Detection by Hyung Rae Lee, Wounsuk Rhee, Sam Yeol Chang, Bong-Soon Chang, Hyoungmin Kim

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A survey of MRI-based brain tissue segmentation using deep learning by Liang Wu, Shirui Wang, Jun Liu, Lixia Hou, Na Li, Fei Su, Xi Yang, Weizhao Lu, Jianfeng Qiu, Ming Zhang, Li Song

Subjects: “…Brain tissue segmentation…”
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Learning tissue representation by identification of persistent local patterns in spatial omics data by Jovan Tanevski, Loan Vulliard, Miguel A. Ibarra-Arellano, Denis Schapiro, Felix J. Hartmann, Julio Saez-Rodriguez

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Deep Learning for Multi-Tissue Cancer Classification of Gene Expressions (GeneXNet) by Tarek Khorshed, Mohamed N. Moustafa, Ahmed Rafea

“…Our proposed GeneXNet provides capabilities of detecting genetic alterations driving cancer progression by learning genomic signatures across multiple tissue types without requiring the prerequisite of gene feature selection. …”
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Deep Learning-Enabled Integration of Histology and Transcriptomics for Tissue Spatial Profile Analysis by Yongxin Ge, Jiake Leng, Ziyang Tang, Kanran Wang, Kaicheng U, Sophia Meixuan Zhang, Sen Han, Yiyan Zhang, Jinxi Xiang, Sen Yang, Xiang Liu, Yi Song, Xiyue Wang, Yuchen Li, Junhan Zhao

“…Spatially resolved transcriptomics enable comprehensive measurement of gene expression at subcellular resolution while preserving the spatial context of the tissue microenvironment. While deep learning has shown promise in analyzing SCST datasets, most efforts have focused on sequence data and spatial localization, with limited emphasis on leveraging rich histopathological insights from staining images. …”
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Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…Recently, it has been demonstrated that RS can perform an accurate classification of chondrosarcoma tissues. Chondrosarcoma is a cancer of bones, that can occur in the soft tissues near the bones. …”
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Bioinformatics meets machine learning: identifying circulating biomarkers for vitiligo across blood and tissues by Qiyu Wang, Jingwei Yuan, Jingwei Yuan, Mengdi Zhang, Haiyan Jia, Hongjie Lu, Yan Wu

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Deep learning deciphers the related role of master regulators and G-quadruplexes in tissue specification by Artem Bashkatov, Andrey Andreasyan, Dmitry Konovalov, Alan Herbert, Maria Poptsova

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Grading of Melanoma Tissues by Raman MicroSpectroscopy by Gianmarco Lazzini, Mario D’Acunto

“…The work demonstrated excellent Machine Learning performances in classifying the tissues under investigation.…”
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Rapid Colorectal Tissue Classification Using Data-Driven Raman Techniques by Jakub Tomes, Daniela Janstova, Shayestegan Mohsen, Alla Sinica, Zuzana Kovacova, Jaromir Petrtyl, Jan Mares

“…In this study, we present a rapid procedure for Raman tissue analysis and classification using machine learning methods, including both supervised and hybrid supervised-unsupervised approaches, to distinguish between healthy and pathological cases based on Raman spectroscopy data. …”
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