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

Subjects: “…Deep learning…”
Get full text

Digital Pathology Tailored for Assessment of Liver Biopsies by Alina-Iuliana Onoiu, David Parada Domínguez, Jorge Joven

Subjects: Get full text

Imputing single-cell protein abundance in multiplex tissue imaging by Raphael Kirchgaessner, Cameron Watson, Allison Creason, Kaya Keutler, Jeremy Goecks

“…Here, we apply machine learning to impute single-cell protein abundance using multiplex tissue imaging data from a breast cancer cohort. …”
Get full text

Three-dimensional single-cell transcriptome imaging of thick tissues by Rongxin Fang, Aaron Halpern, Mohammed Mostafizur Rahman, Zhengkai Huang, Zhiyun Lei, Sebastian J Hell, Catherine Dulac, Xiaowei Zhuang

“…Here, we present a thick-tissue three-dimensional (3D) MERFISH imaging method, which uses confocal microscopy for optical sectioning, deep learning for increasing imaging speed and quality, as well as sample preparation and imaging protocol optimized for thick samples. …”
Get full text

Evaluating Neural Network Performance in Predicting Disease Status and Tissue Source of JC Polyomavirus from Patient Isolates Based on the Hypervariable Region of the Viral Genome by Aiden M. C. Pike, Saeed Amal, Melissa S. Maginnis, Michael P. Wilczek

“…The PML status and tissue source models were 100% and 87.8% accurate, respectively. …”
Get full text

Comparative analysis of convolutional neural networks and transformer architectures for breast cancer histopathological image classification by Bo Yuan, Yudie Hu, Yan Liang, Yutong Zhu, Lingyu Zhang, Shimin Cai, Rui Peng, Xianbin Wang, Zheng Yang, Jinhui Hu

Subjects: Get full text

A Literature Review on Artificial Intelligence in Dermatological Diagnosis and Tissue Microscopy by Paul-Vasile Vezeteu, Andrei-Daniel Andronescu, Dumitru-Iulian Nastac

Get full text

CRITICAL THINKING AND BIOLOGICAL LITERACY: RELATIONSHIP WITH CONCEPTUAL UNDERSTANDING OF PLANT TISSUE by Rizhal Hendi Ristanto, Mieke Miarsyah, Shinta Alief Fitrianingtyas

“…Biology learning currently requires students to have critical thinking ability and biological literacy so that they can improve conceptual understanding. …”
Get full text

Sharing and Specificity of Co-expression Networks across 35 Human Tissues. by Emma Pierson, GTEx Consortium, Daphne Koller, Alexis Battle, Sara Mostafavi, Kristin G Ardlie, Gad Getz, Fred A Wright, Manolis Kellis, Simona Volpi, Emmanouil T Dermitzakis

“…To understand the regulation of tissue-specific gene expression, the GTEx Consortium generated RNA-seq expression data for more than thirty distinct human tissues. …”
Get full text

Final assessment tool quality of the subject Cell, Tissues and Integumentary System by Marlen Llanes Torres, Roxana Gómez Vilela, Galia Ibis Pérez Rumbaut, Laura Naranjo Hernández, Zulema Tamara Mesa Montero, Grey Alicia Crespo Lechuga

“…<p><strong>Background:</strong> when an assessment tool is used, it must conform to rigorous quality standards; defects in its preparation have negative effects on the teaching-learning process.<br /><strong>Objective:</strong> to evaluate the quality of the ordinary examination of the Cell Tissues and Integumentary System subject through the level of difficulty and the power of the instrument discrimination.…”
Get full text

UltRAP‐Net: Reverse Approximation of Tissue Properties in Ultrasound Imaging by Yingqi Li, Ka‐Wai Kwok, Magdalena Wysocki, Nassir Navab, Zhongliang Jiang

“…However, its capability to reveal the underlying tissue properties remains underexplored. A physics‐constrained learning framework is studied to reversely approximate tissue property representations from multiple B‐mode images acquired with varying dynamic ranges. …”
Get full text

Integrating Modern Technologies into Traditional Anterior Cruciate Ligament Tissue Engineering by Aris Sopilidis, Vasileios Stamatopoulos, Vasileios Giannatos, Georgios Taraviras, Andreas Panagopoulos, Stavros Taraviras

“…Finally, we highlight the benefits of incorporating new technologies like artificial intelligence and machine learning that could revolutionize tissue engineering.…”
Get full text

Enhancing chronic wound assessment through agreement analysis and tissue segmentation by Ana C. Morgado, Rafaela Carvalho, Ana Filipa Sampaio, Maria J. M. Vasconcelos

“…In this work, inter-rater agreement analyses were conducted to evaluate the consistency of manual annotations performed by multiple experts and an automated methodology for tissue segmentation leveraging advanced deep learning techniques is proposed. …”
Get full text

Macrophages on the run: Exercise balances macrophage polarization for improved health by Yotam Voskoboynik, Andrew D. McCulloch, Debashis Sahoo

Subjects: Get full text

Predictive Modeling of the Softness of Facial Tissue Products: A Spectral Analysis Approach by Yong Ju Lee, Ji Eun Cha, Geon-Woo Kim, Tai-Ju Lee, Hyoung Jin Kim

“…This work highlights the potential of combining spectral analysis and machine learning for objective softness evaluation.…”
Get full text

Chemoreactomic study of fonturacetam effects: molecular mechanisms of influence on adipose tissue metabolism by O. A. Gromova, I. Yu. Torshin

“…Chemoreactomic, pharmacoinformatic and chemoneurocytological methods of molecule properties analyzis are based on chemoreactomic methodology – the latest direction in the application of machine learning systems in the field of postgenomic pharmacology. …”
Get full text

Unsupervised spatiotemporal classification of deformation patterns of embryonic tissues matches their fate map by David Pastor-Escuredo, Benoît Lombardot, Thierry Savy, Adeline Boyreau, René Doursat, Jose M. Goicolea, Andrés Santos, Paul Bourgine, Juan C. del Álamo, María J. Ledesma- Carbayo, Nadine Peyriéras

“…Finite deformation analysis along cell trajectories and unsupervised machine learning are applied to obtain reduced-order models condensing the collective cell motions, delineating tissue domains with distinct 4D biomechanical behavior. …”
Get full text

Towards interactive AI-authoring with prototypical few-shot classifiers in histopathology by Petr Kuritcyn, Rosalie Kletzander, Sophia Eisenberg, Thomas Wittenberg, Volker Bruns, Katja Evert, Felix Keil, Paul K. Ziegler, Katrin Bankov, Peter Wild, Markus Eckstein, Arndt Hartmann, Carol I. Geppert, Michaela Benz

Subjects: Get full text

Exploring Deep Clustering Methods in Vibro-Acoustic Sensing for Enhancing Biological Tissue Characterization by Robin Urrutia, Diego Espejo, Montserrat Guerra, Karin Vio, Thomas Suhn, Nazila Esmaeili, Axel Boese, Patricio Fuentealba, Alfredo Illanes, Christian Hansen, Victor Poblete

“…This study explores the characterization of six tissue types through manifold learning and unsupervised clustering, utilizing vibro-acoustic (VA) signals collected from manual palpation experiments. …”
Get full text

High resolution tissue and cell type identification via single cell transcriptomic profiling. by Muyi Liu, Suilan Zheng, Hongmin Li, Bruce Budowle, Le Wang, Zhaohuan Lou, Jianye Ge

“…By incorporating a crucial and unique reference cell quality differentiation phase of targeting only high confident cells as reference, scTissueID achieved better and consistent performance in determining cell and tissue types compared to 8 state-of-art single cell annotation pipelines and 6 widely adopted machine learning algorithms, as demonstrated through a large-scale and comprehensive comparison study using both forensic-relevant and Human Cell Atlas (HCA) data. …”
Get full text