Results 201 to 210 of about 51,355 (218)

Protective Effects of Myrtus communis Essential Oil Against Bisphenol A‐Induced Metabolic Dysfunction‐Associated Fatty Liver Disease in Wistar Rats

Food Science &Nutrition, Volume 14, Issue 2, February 2026.
Exposure to bisphenol A (BPA) induced hepatic steatosis associated with metabolic dysfunction (MASLD) in Wistar rats, characterized by dyslipidemia, oxidative stress, and hepatic steatosis. Co‐treatment with essential oil of myrtus communis (EOMC) improved markers of liver function, lipid profile, and antioxidant status, with histological improvement ...
Mhimdi Mariem, Selmi Slimen, Amira Zammali, Manel Hraoui, Soumaya Wahabi, Dallacqua Stefano, Sebai Hichem   +6 more
wiley   +1 more source

Genetically Predicted Homocysteine Levels and B Vitamins on Sarcopenia‐Related Traits: Insights From an Observational and Mendelian Randomization Analysis

Food Science &Nutrition, Volume 14, Issue 2, February 2026.
We employed Mendelian randomization analysis and longitudinal cohort data to identify a causal relationship between genetically predicted high Hcy levels and low grip strength as well as low appendicular lean mass. In the clinical cohort, individuals with persistent medium and high levels of Hcy had a significantly increased risk of sarcopenia, and a ...
Caizheng Yang, Shanshan Ge, Fangying Tian, Yan Jiang, Yue Guo, Xiumei Wang, Hongwei Wang   +6 more
wiley   +1 more source

Investigating the Utility of Explainable Artificial Intelligence for Neuroimaging‐Based Dementia Diagnosis and Prognosis

Human Brain Mapping, Volume 47, Issue 2, February 1, 2026.
Artificial intelligence has the potential to enhance clinical decision making, but complex black box models can be difficult to interpret and trust. Explainable artificial intelligence methods aim to open the black box by highlighting which features are driving the model's prediction.
Sophie A. Martin, An Zhao, Jiongqi Qu, Phoebe Imms, Andrei Irimia, Frederik Barkhof, James H. Cole, Alzheimer's Disease Neuroimaging Initiative   +7 more
wiley   +1 more source

Deep cytomorphology identifies erythroid skewing and monocytic morphology to predict TKI sensitivity in CML patients

HemaSphere, Volume 10, Issue 2, February 2026.
Abstract The cellular composition of the chronic myeloid leukemia (CML) bone marrow (BM) beyond granulocyte enrichment remains poorly understood. We analyzed 1548 routinely stained BM aspirate slides from 598 patients across seven sites using deep learning‐based image analysis to identify cytomorphological markers predictive of major molecular response.
Katariina Luukkainen, Mikko Purhonen, Mikael Tatun, Kevin Hung, Oda Tafjord, Henri Sundquist, Stina Söderlund, Shady Adnan‐Awad, Anni Dohlen, Johanna Heikkinen, Perttu Koskenvesa, Lotta Joutsi‐Korhonen, Anna Lempiäinen, Sanna Siitonen, Satu Mustjoki, Naranie Shanmuganathan, Coral Bryce, Signe Danielsson, Henrik Hjorth‐Hansen, Ulla Olsson‐Strömberg, Takashi Kumagai, Shinya Kimura, David M. Ross, Oscar Brück   +23 more
wiley   +1 more source

Peripheral blood smear analysis: A comparison of GPT‐4o and supervised deep learning models

Clinical and Translational Discovery, Volume 6, Issue 1, February 2026.
Mobina Shrestha, Salina Dahal, Vishal Mandal, Amir Babu Shrestha   +3 more
wiley   +1 more source

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A-ViT: Adaptive Tokens for Efficient Vision Transformer

Computer Vision and Pattern Recognition, 2021
We introduce A - ViT, a method that adaptively adjusts the inference cost of vision transformer (ViT) for images of different complexity. A - ViT achieves this by automatically reducing the number of tokens in vision transformers that are processed in ...
Hongxu Yin, Arash Vahdat, J. Álvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov   +5 more
semanticscholar   +1 more source

HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative Perception with Vision Transformer

IEEE International Conference on Computer Vision, 2023
Vehicle-to-Vehicle technologies have enabled autonomous vehicles to share information to see through occlusions, greatly enhancing perception performance.
Hao Xiang, Runsheng Xu, Jiaqi Ma
semanticscholar   +1 more source

I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference

IEEE International Conference on Computer Vision, 2022
Vision Transformers (ViTs) have achieved state-of-the-art performance on various computer vision applications. However, these models have considerable storage and computational overheads, making their deployment and efficient inference on edge devices ...
Zhikai Li, Qingyi Gu
semanticscholar   +1 more source

Your ViT is Secretly an Image Segmentation Model

Computer Vision and Pattern Recognition
Vision Transformers (ViTs) have shown remarkable performance and scalability across various computer vision tasks. To apply single-scale ViTs to image segmentation, existing methods adopt a convolutional adapter to generate multi-scale features, a pixel ...
Tommie Kerssies, Niccolò Cavagnero, Alexander Hermans, Narges Norouzi, Giuseppe Averta, Bastian Leibe, Gijs Dubbelman, Daan de Geus   +7 more
semanticscholar   +1 more source

Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection

arXiv.org, 2023
This work studies a challenging and practical issue known as multi-class unsupervised anomaly detection (MUAD). This problem requires only normal images for training while simultaneously testing both normal and anomaly images across multiple classes ...
Jiangning Zhang, Xuhai Chen, Yabiao Wang, Chengjie Wang, Yong Liu, Xiangtai Li, Ming-Hsuan Yang, Dacheng Tao   +7 more
semanticscholar   +1 more source