Current AI Applications and Challenges in Oral Pathology by Zaizhen Xu, Alice Lin, Xiaoyuan Han

“…Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL) techniques such as convolutional neural networks (CNNs) and natural language processing (NLP), has shown remarkable promise in image analysis and clinical documentation in oral pathology. …”
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A refined lion optimizer for deep learning by Jian Rong, Chenhao Ma, Qinghui Zhang, Yong Cao, Weili Kou

“…The FasterNet, EfficientNetV2 and the YOLOV8 on ImageNet1k dataset are trained without warm up for classification by leveraging the RLion optimizer. …”
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A Deep Longitudinal Model for Mild Cognitive Impairment to Alzheimer’s Disease Conversion Prediction in Low-Income Countries by Adeem Akhtar, Sidra Minhas, Nosheen Sabahat, Aasia Khanum

“…After normalization and ranking of longitudinal data, the deep neural network regression model is trained and tuned to forecast the next in-sequence biomarker value using two previous follow-up readings for each marker. …”
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Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI by Khan Muhammad Adnan, Taher M. Ghazal, Muhammad Saleem, Muhammad Sajid Farooq, Chan Yeob Yeun, Munir Ahmad, Sang-Woong Lee

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Neural decoding of Aristotle tactile illusion using deep learning-based fMRI classification by Eunji Lee, Eunji Lee, Ji-Hyun Kim, Jaeseok Park, Jaeseok Park, Sung-Phil Kim, Taehoon Shin, Taehoon Shin, Taehoon Shin

“…This study aimed to identify brain regions involved in the Aristotle illusion using functional magnetic resonance imaging (fMRI) and deep learning-based analysis of fMRI data.MethodsWhile three types of tactile stimuli (Aristotle, Reverse, Asynchronous) were applied to thirty participants’ fingers, we collected fMRI data, and recorded the number of stimuli each participant perceived. …”
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Methodological Considerations in Conducting an Olfactory fMRI Study by Faezeh Vedaei, Mohammad Fakhri, Mohammad Hossein Harirchian, Kavous Firouznia, Yones Lotfi, Mohammad Ali Oghabian

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Geographic disparities in perioperative and mid-term outcomes after elective infrarenal endovascular aneurysm repair by Lisa Vi, MD, Rashi Gupta, MSc, Naomi Eisenberg, PT, MEd, Miranda Witheford, MD, PhD, FRCSC

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Investigation of 3D iris morphology early alteration after implantable collamer lens implantation by using SS-OCT by Zhengwei Zhang, Shuimiao Chang, Kaiwen Li, Jinhan Yao, Zhao Wang, Jiewei Liu, Lin Jiang, Feiyan Chai, Xiaogang Wang

“…Results: Forty-six eyes of 27 patients (average age, 26.0 ± 5.3 years) were included in the final data analysis. The spherical equivalent ranged from −15.75 to −4.00 diopters (D). …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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Formation of Dialogic Interactions in Children with Autism Spectrum Disorders by Тетяна Скрипник, Ольга Лозова

“…Methods. The methods of analysis, systematization, generalization and theoretical triangulation of scientific data have been applied. …”
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Automated interpretation of PD-L1 CPS based on multi-AI models integration strategy in gastric cancer by Ting Han, Meng Zhuo, Ziyu Song, Peilin Chen, Shiting Chen, Wei Zhang, Yuanyuan Zhou, Hong Li, Dadong Zhang, Xiaolin Lin, Zebing Liu, Xiuying Xiao

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Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning by Yongguang Liang, Jingru Yang, Shuoyang Wei, Yanfei Liu, Shumeng He, Kang Zhang, Jie Qiu, Bo Yang

“…A total of three criteria-calibration approaches to solve the data imbalance problem in dose prediction were introduced and compared, including Prediction Tolerance function on uTPS (United Imaging Healthcare Co., Ltd., Shanghai), transfer learning, and mixture density network. …”
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Depth-to-scalp spatiotemporal dynamics for stereo-EEG by Tal Benoliel, Oshrit Arviv, Diya Doufish, Netaniel Rein, Yuval Harpaz, Evgeny Tsizin, Michal Balberg, Sami Heymann, Zvi Israel, Mordekhay Medvedovsky, Dana Ekstein

“…Our novel analysis highlights the importance of temporal, and not just spatial, spike dynamics within the epileptic network, may be used to validate depth electrode placement and aid in understanding the epileptic network.…”
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Artificial Intelligence-Driven Multi-Agent System for Enhanced Radiology Workflow and Decision Support by Kristijan CINCAR, Todor IVAŞCU

“…The Hospital Scheduler Agent (SA) would assign a time slot allocated for radiological examinations, while the Hospital Resource Agent (RA) guarantees the availability of appropriate imaging equipment and medical personnel. During the whole process of diagnosis, the Radiology Monitoring Agent (RMA) captures imaging data for analysis, identifies those data that have real-time potential anomalies, and optimizes imaging protocols. …”
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SBRT for bridging and downstaging HCC before transplant by Zhihao Li, Michael Yan, Marco P.A.W. Claasen, Luckshi Rajendran, Christian T.J. Magyar, Saheli Saha, Cameron Lee, Nazia Selzner, Elmar Jaeckel, Anand Ghanekar, Mark Cattral, Blayne A. Sayed, Markus Selzner, Ian McGilvray, Chaya Shwaartz, Trevor Reichman, Grainne M. O’Kane, Arndt Vogel, Robert C. Grant, Tae Kyoung Kim, Catherine Soo-Yee Naidoo, Ali Hosni, Rebecca Wong, Aruz Mesci, Jelena Lukovic, Aisling Barry, John Kim, Laura A. Dawson, Gonzalo Sapisochin

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Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm by Scott Isherwood, Sarah A Kemp, Steven Miletić, Niek Stevenson, Pierre-Louis Bazin, Birte Forstmann

“…Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task to examine this network. …”
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Review article developing safety and enjoyment factors in karst cave tourism model: review discussing the model, factors and results by Trio Yonathan Teja Kusuma, Susy Susmartini, Bambang Suhardi, Lobes Herdiman

“…The systematic literature review method uses the PRISMA method and bibliometric analysis uses Vosviewer. The data source was obtained from Scopus for the 2018–2023 period. …”
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Research Progress and Prospects of Minimally Invasive Surgical Instrument Segmentation Methods Based on Artificial Intelligence by Weimin CHENG, Xiaohua WU, Jing XIONG

“…Surgical instrument segmentation is a highly promising technology that can enhance the performance of minimally invasive endoscopic imaging systems, surgical video analysis systems, and other related systems. …”
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Investigation on potential bias factors in histopathology datasets by Farnaz Kheiri, Shahryar Rahnamayan, Masoud Makrehchi, Azam Asilian Bidgoli

“…Abstract Deep neural networks (DNNs) have demonstrated remarkable capabilities in medical applications, including digital pathology, where they excel at analyzing complex patterns in medical images to assist in accurate disease diagnosis and prognosis. …”
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Machine learning Techniques for Spondylolisthesis Diagnosis: a review by Rahma Rabee Aziz, Mohammed S. Jarjees, Mohammad R. Aziz, Ali Asim Hameed

“…Notably, these findings address a gap in previous research by measuring spondylolisthesis severity and distinguishing between normal and abnormal spines. The analysis emphasizes the significance of selecting the appropriate modality and data quality, with X-rays predominating as the preferred imaging technique. …”
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