Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification by Miao Yu, Zhenqi Ye, Zixin Ye, Yaping Wu, Xiang Wu

“…Results Eighty-three DE-NRGs were identified and mainly correlated with multiple periodontitis-related pathways. Then, a diagnostic NRG signature based on 7-hub NRGs (LPAR3, CXCR4, F3, MAPK7, KCNN3, SYK, and HIF1A) was constructed using two different machine learning algorithms. …”
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Validation of the Recording of Acute Exacerbations of COPD in UK Primary Care Electronic Healthcare Records. by Kieran J Rothnie, Hana Müllerová, John R Hurst, Liam Smeeth, Kourtney Davis, Sara L Thomas, Jennifer K Quint

“…We selected dates of possible AECOPD based on 15 different algorithms between January 2004 and August 2013. …”
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Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches by Xinmin Jin, Lei Li, Xiaoyan Hu, Pengfei Bi, Song Zhang, Qian Wang, Zhongwei Xiao, Hua Yang, Tongtong Liu, Lifang Feng, Jinhuan Wang

“…Objectives: This study aimed to explore the association between urinary metal element levels and sarcopenia across different glucose metabolic states using multi-omics clustering algorithms and machine learning models, and to identify diagnostic biomarkers. …”
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Multimodal approaches and AI-driven innovations in dementia diagnosis: a systematic review by Revati M. Wahul, Sarita Ambadekar, Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Manisha A. Dudhedia, Varsha Gaikwad, Bhavana Kanawade, J. R. Pansare, Balaji Bodkhe, S. H. Gawande

“…As a systematic literature review, this paper outlines the intricacies of dementia’s pathophysiology of dementia by addressing the complexity of dementia as a construct, how different types of clinical paths can happen, how neuronal atrophy occurs along different cerebral domains, and when the critical diagnostic thresholds are met. …”
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Comparison of Radiomics and conventional SUVr methods for Alzheimer’s disease classification using AV45 PET imaging by Haiyan Gao, Arui Tan, Junhao Wu, Zhen Cao, Ziyang Zhu, Wei Zhang

“…Feature importance was ranked using a random forest algorithm, and three models were constructed: an SUVr model, a radiomics model, and a combined model. …”
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Whole-Body Diffusion-Weighted Magnetic Resonance Imaging and Positron Emission Tomography Combined with Computed Tomography in the Staging of Lymphomas by S. A. Kharuzhyk, E. A. Zhavrid, A. V. Dzyuban, K. V. Poddubnyy, E. V. Sukolinskaya, O. A. Kalenik

“…The new lymphoma staging algorithm based on whole-body DW-MRI is superior to PET/CT and PET/CT with BM biopsy.…”
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Identification and mechanism analysis of biomarkers related to butyrate metabolism in COVID-19 patients by Wenchao Zhou, Hui Li, Juan Zhang, Changsheng Liu, Dan Liu, Xupeng Chen, Jing Ouyang, Tian Zeng, Shuang Peng, Fan Ouyang, Yunzhu Long, Yukun Li

“…Six machine learning algorithms were employed to determine the best model for identifying biomarkers, and receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic value of the biomarkers in COVID-19. …”
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Artificial intelligence for diagnosing rare bone diseases: a global survey of healthcare professionals by Behnam Javanmardi, Rebekah L. Waikel, Tinatin Tkemaladze, Shahida Moosa, Alexander Küsshauer, Jean Tori Pantel, Minu Fardipour, Peter Krawitz, Benjamin D. Solomon, Klaus Mohnike

“…Although around half of the participants (n = 45) have concerns about AI-related errors and consider the explainability of AI algorithms to be very (42/103) or extremely (9/103) important, 81% of the respondents report that they are somewhat (n = 39) or extremely (n = 45) likely to consider integrating image recognition AI into their current diagnostic workflow. …”
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Unstructured Electronic Health Records of Dysphagic Patients Analyzed by Large Language Models by Luisa Neubig, Deirdre Larsen, Melda Kunduk, Andreas M. Kist

“…We utilize clustering algorithms on the extracted diagnostic features to identify distinct groups of patients who share similar pathophysiological swallowing dysfunctions.Results: We found that basic NLP techniques often provide limited insights due to the high variability of the data. …”
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Systematic review and meta-analysis of deep learning for MSI-H in colorectal cancer whole slide images by Huo Li, Jing Qin, Zhongzhuan Li, Rong Ouyang, Zhixin Chen, Shijiang Huang, Shufen Qin, Qiliang Huang

“…Abstract This meta-analysis evaluated diagnostic performance of deep learning (DL) algorithms using whole slide images (WSIs) for detecting microsatellite instability-high (MSI-H) in colorectal cancer (CRC). …”
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Impact of Damping Models in Damage Identification by Michael Souza, Daniel Castello, Ney Roitman, Thiago Ritto

“…Several damage identification approaches are based on computational models, and their diagnostics depend on the set of modelling hypotheses adopted when building the model itself. …”
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P85 | ALTERATION OF SUBMUCOSAL AND MYENTERIC GANGLIA IN SEVERE GUT DYSMOTILITY: A QUANTITATIVE MORPHOMETRIC ANALYSIS

“…While requiring further validation, this study provides proof of concept for a new diagnostic algorithm for SD, based on the stepwise assessment of morphometric indices, with a focus on the myenteric plexus. …”
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Perfusion Computed Tomography in the Diagnosis of Colonic Diverticular Disease and its Complications by M. V. Timerbulatov, A. F. Itkulov, D. E. Baikov, A. A. Ibatullin, M. M. Khafizov

“…Since PCT is able to detect the difference of microcirculation parameters in inflammatory and malignant processes, it can be used in the diagnostic algorithm to determine further treatment strategy.…”
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Cutting guides in mandibular tumor ablation: Are we as accurate as we think? by Omar Suhaym, Loren Moles, Nicholas Callahan

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Diagnosis and management of metabolic dysfunction- associated steatotic liver disease in South Asians- A clinical review by Prajith Raj Ramesh, Priya Krishnan, Samyuktha Prabu, Varshini Srinivasan, Varalakshmi Niranjan

“…More research is needed to formulate guidelines and algorithm that are specific for the South Asian population.…”
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ACQUIRED HAEMOPHILIA A: AN INTRIGUING DISEASE by Maria Gabriella Mazzucconi, Erminia Baldacci, Antonietta Ferretti, Cristina Santoro

“…The disease may be underdiagnosed in the elderly. The diagnostic algorithm is based on an isolated prolonged activated partial thromboplastin time, normal thrombin time, absence of Lupus Anticoagulant and a mixing test that reveals the presence of an inhibitor: the finding of reduced FVIII activity and the detection of neutralising autoantibodies against FVIII lead to diagnosis. …”
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Artificial Intelligence Precision Recognition and Auxiliary Diagnosis of Dental X-ray Panoramic Images Based on Deep Learning by Liu Riming, Gao Zhenshan

“…Objective: This study aims to explore the application of deep learning algorithms in dental X-ray panoramic images, particularly for the automatic segmentation of dental caries and identification of wisdom tooth types, in order to improve the accuracy and efficiency of dental diagnosis and assist doctors in formulating precise treatment plans. …”
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Applications of Artificial Intelligence in Vasculitides: A Systematic Review by Mahmud Omar, Reem Agbareia, Mohammad E. Naffaa, Abdulla Watad, Benjamin S. Glicksberg, Girish N. Nadkarni, Eyal Klang

“…AI models achieved high diagnostic performance in Kawasaki disease, with sensitivities up to 92.5% and specificities up to 97.3%. …”
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Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis. by Nabila Kazmi, Tom R Gaunt

“…Three different feature optimisation algorithms were devised which identified two discriminating sets of genes, one using MI and normal controls (total genes = 6) and another one using MI and unstable angina patients (total genes = 7). …”
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Revolutionizing Cardiac Risk Assessment: AI-Powered Patient Segmentation Using Advanced Machine Learning Techniques by Joan D. Gonzalez-Franco, Alejandro Galaviz-Mosqueda, Salvador Villarreal-Reyes, Jose E. Lozano-Rizk, Raul Rivera-Rodriguez, Jose E. Gonzalez-Trejo, Alexei-Fedorovish Licea-Navarro, Jorge Lozoya-Arandia, Edgar A. Ibarra-Flores

“…Interestingly, no significant differences in blood pressure were observed between the groups. …”
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