Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions by Santosh R. Patil, Mohmed Isaqali Karobari

“…The review methodology involves a critical analysis of existing literature, highlighting advancements in diagnostic imaging, predictive analytics, and procedural assistance. …”
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Genomic structural equation modeling reveals latent phenotypes in the human cortex with distinct genetic architecture by Rajendra A. Morey, Yuanchao Zheng, Henry Bayly, Delin Sun, Melanie E. Garrett, Marianna Gasperi, Adam X. Maihofer, C. Lexi Baird, Katrina L. Grasby, Ashley A. Huggins, Courtney C. Haswell, Paul M. Thompson, Sarah Medland, Daniel E. Gustavson, Matthew S. Panizzon, William S. Kremen, Caroline M. Nievergelt, Allison E. Ashley-Koch, Mark W. Logue

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Using artificial intelligence methods for shear travel time prediction: A case study of Facha member, Sirte basin, Libya by Bahia Ben Ghawar, Moncef Zairi, Samir Bouaziz

“…Based on principle component analysis, two wireline data sets were chosen to build intelligent models for prediction of shear travel time. …”
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Research Progress on Micro/Nanopore Flow Behavior by Jinbo Yu, Meng Du, Yapu Zhang, Xinliang Chen, Zhengming Yang

“…Moreover, the integration of artificial intelligence (e.g., data-driven modeling and physics-informed neural networks) is accelerating data interpretation and multiscale modeling, offering improved predictive capabilities. …”
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From black box AI to XAI in neuro-oncology: a survey on MRI-based tumor detection by Asmita, Praveen Mittal

“…It also provides an in-depth analysis of widely used MRI datasets, highlighting persistent challenges such as data imbalance, overfitting, and variability across imaging domains. …”
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Clinical and cost-effectiveness of detailed anomaly ultrasound screening in the first trimester: a mixed-methods study by Jehan N Karim, Helen Campbell, Pranav Pandya, Edward C F Wilson, Zarko Alfirevic, Trish Chudleigh, Elizabeth Duff, Jane Fisher, Hilary Goodman, Lisa Hinton, Christos Ioannou, Edmund Juszczak, Louise Linsell, Heather L Longworth, Kypros H Nicolaides, Anne Rhodes, Gordon Smith, Basky Thilaganathan, Jim Thornton, Gillian Yaz, Oliver Rivero-Arias, Aris T Papageorghiou

“…Design Systematic review and meta-analysis. Nationwide survey. Analysis of National Congenital Anomaly Disease Registry data. …”
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Harnessing Deep Learning for Lung Cancer Detection and Prevention: A Comprehensive Survey by Tidke Dipika, Banait Satish S.

“…This survey investigates how deep learning is changing the landscape of lung cancer detection and prevention, with attention to recent breakthroughs in medical imaging analysis. Deep learning models have had some success in accurately classifying lung nodules and other CT abnormalities using convolutional neural networks (CNNs), as well as advanced architecture such as ResNet and U-Net. …”
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Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis by Serena Dattola, Augusto Ielo, Giuseppe Varone, Giuseppe Varone, Alberto Cacciola, Angelo Quartarone, Lilla Bonanno

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Enhanced Detection and Segmentation of Brain Tumors Using a Dense BW-CNN Approach by Sangeeta Kakarwal, Rahul Mapari, Anuj Kumar Jain, Vipin Sharma, Pranoti Prashant Mane, Jambi Ratna Raja Kumar, Ranjan K. Pradhan

“…However, manual MRI data analysis is time-consuming and prone to errors. …”
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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“…The patient data used in these studies comprised demographics, clinical characteristics, various types of imaging (9/23, 39%), and electrophysiological signals (7/23, 30%). …”
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Impact of climate change on landslides along N-15 Highway, northern Pakistan by Muhammad Ramzan, Peng Cui, Daniya Ualiyeva, Hamza Mukhtar, Nazir Ahmed Bazai, Muhammad Aslam Baig

“…We collected a complete landslide inventory using 455 satellite images from 1990 to 2023 and ground surveys. We also analysed the relationship between landslides and climate change over the period of 1990–2023, encompassing soil moisture, vegetation, precipitation, temperature and snow cover. …”
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Advanced Chemometric Techniques for Environmental Pollution Monitoring and Assessment: A Review by Shaikh Manirul Haque, Yunusa Umar, Abuzar Kabir

“…Chemometrics has emerged as a powerful approach for deciphering complex environmental systems, enabling the identification of pollution sources through the integration of faunal community structures with physicochemical parameters and in situ analytical data. Leveraging advanced technologies—including satellite imaging, drone surveillance, sensor networks, and Internet of Things platforms—chemometric methods facilitate real-time and longitudinal monitoring of both pristine and anthropogenically influenced ecosystems. …”
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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Advances in machine learning, deep neural networks, and multi-omics data analysis enable precise prognostication, tailored antiretroviral therapy, and early detection of drug resistance. …”
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Single-cell sequencing uncovers a high ESM1-expression endothelial cell subpopulation associated with bladder cancer progression and the immunosuppressive microenvironment by Yifeng Qiu, Yuhan Wang, Jiahe Liu, Baohua Liu, Kai Sun, Qi Hou

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The correlation between neutrophil/lymphocyte ratio and the MRI burden and cognitive function in patients with cerebral small vessel disease by Mengyao Zhao, Mengyao Zhao, Xiaohua Xie, Xiaohua Xie, Zhiwei Hao, Zhiwei Hao, Mengsi Ren, Zhenjie Teng, Zhenjie Teng, Jing Xu, Jing Xu, Chunhui Shan, Yanhong Dong, Yanhong Dong, Peiyuan Lv, Peiyuan Lv

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Baseline 18F-FDG PET/CT parameters in predicting the efficacy of immunotherapy in non-small cell lung cancer by Lu Zheng, Lu Zheng, Yanzhu Bian, Yanzhu Bian, Yujing Hu, Congna Tian, Xinchao Zhang, Shuheng Li, Xin Yang, Yanan Qin

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AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review by Sandra López Gordo, Elena Ramirez-Maldonado, Maria Teresa Fernandez-Planas, Ernest Bombuy, Robert Memba, Rosa Jorba

“…These models integrate clinical, laboratory, and imaging data, including radiomics features, and are useful in diagnostic and prognostic accuracy in AP. …”
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Occupational stress among Namibian diagnostic radiographers during the COVID-19 pandemic by Festus Shidolo, Aladdin Speelman, Valdiela Daries

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Uncertainty-aware deep learning in healthcare: A scoping review. by Tyler J Loftus, Benjamin Shickel, Matthew M Ruppert, Jeremy A Balch, Tezcan Ozrazgat-Baslanti, Patrick J Tighe, Philip A Efron, William R Hogan, Parisa Rashidi, Gilbert R Upchurch, Azra Bihorac

“…All imaging model architectures used convolutional neural networks or a variation thereof. …”
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On Usage of Artificial Intelligence for Predicting Neonatal Diseases, Conditions, and Mortality: A Bibliometric Review by Flavio Leandro de Morais, Raysa Carla Leal da Silva, Anna Beatriz Silva, Estefani Pontes Simao, Maria Eduarda Ferro de Mello, Stephany Paula da Silva Canejo, Katia Maria Mendes, Waldemar Brandao Neto, Jackson Raniel Florencio da Silva, Maicon Herverton Lino Ferreira da Silva Barros, Patricia Takako Endo

“…Results: The results show that the United States, China and the United Kingdom lead scientific production and international collaborations. 12 neonatal diseases were identified, with emphasis on “retinopathy of prematurity”, “necrotizing enterocolitis” and “bronchopulmonary dysplasia”; 7 clinical conditions, including “prematurity”, “perinatal asphyxia” and “jaundice”; and 5 neonatal outcomes, mainly “sepsis”, “mortality” and “cerebral palsy.” Cluster analysis revealed that studies predominantly use clinical, laboratory, genetic and imaging data, with Logistic Regression, Random Forest and Convolutional. …”
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