Advancing precision dentistry: the integration of multi-omics and cutting-edge imaging technologies—a systematic review by Neelam Das

“…AI tools, including convolutional neural networks and radiomics, led to a 40% reduction in diagnostic time (CI: 33%–45%) and improved lesion classification.ConclusionIntegrating AI with omics and imaging technologies enhances diagnostic precision in dentistry. …”
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Diffusion Model-Based Virtual 3D City Augmentation for EM-Wave Propagation Analysis by Rento Hagiwara, Kazuki Yuasa, Koichi Ichige, Tatsuya Nagao, Takahiro Hayashi

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Deciphering Default Mode Network Dynamics in Alcohol Use Disorder Through Directed Transfer Function Analysis of EEG by Komal Masroor, Danish M. Khan, Hashim Raza Khan, Norashikin Yahya, Kamran Arshad, Khaled Assaleh

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Intelligent Stress Detection Using ECG Signals: Power Spectrum Imaging with Continuous Wavelet Transform and CNN by Rodrigo Mateo-Reyes, Irving A. Cruz-Albarran, Luis A. Morales-Hernandez

“…Electrocardiogram (ECG) signals are pre-processed to remove noise and ensure data quality. The signals are then transformed into two-dimensional images using the continuous wavelet transform (CWT) to identify pattern recognition in the time–frequency domain. …”
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Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…The results indicate that AI models achieve high performance metrics across different imaging modalities. However, the current body of literature lacks comprehensive statistical analysis and randomized controlled trials, underscoring the need for further research to validate these findings in clinical settings. …”
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Dual-coding Contrastive Learning Based on the ConvNeXt and ViT Models for Morphological Classification of Galaxies in COSMOS-Web by Shiwei Zhu, Guanwen Fang, Chichun Zhou, Jie Song, Zesen Lin, Yao Dai, Xu Kong

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Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles by Yu Chen, Hui Zhong, Jianglong Yu

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TECHNOLOGIES FOR DEVELOPING DECISION SUPPORT SYSTEMS FOR THE DIAGNOSIS OF BLOOD DISORDERS USING CONVOLUTIONAL NEURAL NETWORKS by U. V. Maslikova, A. A. Supilnikov

“…We created a database of medical images of  the bone marrow for neural network training. …”
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Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review by Md Shofiqul Islam, Fahmid Al Farid, F. M. Javed Mehedi Shamrat, Md Nahidul Islam, Mamunur Rashid, Bifta Sama Bari, Junaidi Abdullah, Muhammad Nazrul Islam, Md Akhtaruzzaman, Muhammad Nomani Kabir, Sarina Mansor, Hezerul Abdul Karim

“…In this context, artificial intelligence (AI) models, specifically deep learning (DL) networks, emerge as a promising solution in medical image analysis. …”
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Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning by Mahsa Torkaman, Skander Jemaa, Jill Fredrickson, Alexandre Fernandez Coimbra, Alex De Crespigny, Richard A. D. Carano

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Hybrid model for predicting microsatellite instability in colorectal cancer using hematoxylin & eosin-stained images and clinical features by Hangping Wei, Xiaowei Zhang, Zhen Zhou, Jianbin Xie, Weidong Han, Xiaofang Dong

“…Furthermore, to investigate genes associated with MSI, we performed enrichment analysis and constructed a protein-protein interaction (PPI) network using mRNA sequencing data obtained from the TCGA database.ResultsThe fully-supervised pathological model demonstrated promising performance, achieving an AUC of 0.928 in the internal validation cohort, compared to the semi-supervised pathological model’s AUC of 0.786. …”
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Neurobiological correlates of personality dimensions in borderline personality disorder using graph analysis of functional connectivity by Francesca D’Adda, Giovanni Sighinolfi, Micaela Mitolo, Mauro Scala, Lucia Guidi, Lorenzo Motta, Lorenzo Cirignotta, David Neil Manners, Caterina Tonon, Raffaele Lodi, Marco Menchetti

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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Medical image segmentation plays a crucial role in diagnosis and treatment planning, yet faces persistent challenges including limited annotated data, boundary ambiguity, and high computational demands that hinder clinical deployment. …”
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Predicting PD-L1 status in NSCLC patients using deep learning radiomics based on CT images by Jiameng Lu, Xinyi Liu, Xiaoqing Ji, Yunxiu Jiang, Anli Zuo, Zihan Guo, Shuran Yang, Haiying Peng, Fei Sun, Degan Lu

“…Tumor regions of interest (ROI) were semi-automatically segmented based on CT images, and DL features were extracted using Residual Network 50. …”
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Performance Analysis of Costs and Implementation Time Using Earned Value Method on the Distribution Pipe Network Expansion in Samarinda City by Dedy Sugi Hartawan, Wateno Oetomo, Risma Marleno

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Aberrant brain network connectivity related to cognitive and emotional regulation in women with abdominal obesity by Qifu Li, Gaoyangzi Huang, Siwen Zhao, Shumin Zhang, Ziwen Chen, Xin Tang, Xianmei Pei, Ruqin Yang, Zili Liu, Rui Hu, Diwei Tang, Chonghui Xing, Fanrong Liang, Taipin Guo, Yi Lu

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Classification of the ICU Admission for COVID-19 Patients with Transfer Learning Models Using Chest X-Ray Images by Yun-Chi Lin, Yu-Hua Dean Fang

“…The gradient-weighted class activation mapping (Grad-CAM) analysis demonstrated that the TorchX-SBU-RSNA model focused more precisely on the relevant lung regions and reduced the distractions from non-relevant areas compared to the natural image-pre-trained model without data expansion. …”
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Research on Super-Resolution Reconstruction of Coarse Aggregate Particle Images for Earth–Rock Dam Construction Based on Real-ESRGAN by Shuangping Li, Lin Gao, Bin Zhang, Zuqiang Liu, Xin Zhang, Linjie Guan, Junxing Zheng

“…This paper investigates the super-resolution reconstruction technology of coarse granular particle images for embankment construction in earth/rock dams based on Real-ESRGAN, aiming to improve the quality of low-resolution particle images and enhance the accuracy of particle shape analysis. …”
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An annotated high-content fluorescence microscopy dataset with EGFP-Galectin-3-stained cells and manually labelled outlineszenodo by Salma Kazemi Rashed, Malou Arvidsson, Rafsan Ahmed, Sonja Aits

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Deep learning feature-based model for predicting lymphovascular invasion in urothelial carcinoma of bladder using CT images by Bangxin Xiao, Yang Lv, Canjie Peng, Zongjie Wei, Qiao Xv, Fajin Lv, Qing Jiang, Huayun Liu, Feng Li, Yingjie Xv, Quanhao He, Mingzhao Xiao

“…This study aims to develop a deep learning-based model to preoperatively predict lymphovascular invasion status in urothelial carcinoma of bladder using CT images. Methods Data and CT images of 577 patients across four medical centers were retrospectively collected. …”
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