The effectiveness of complex therapy in the treatment of nonspecific vaginitis in women of reproductive age by O.D. Ryazanova, G.I. Reznichenko

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Lithological mapping and spectroscopic studies of carbonatite and clinopyroxenite from Hogenakkal carbonatite complex, India by Saraah Imran, Sourav Bhattacharjee, Ajanta Goswami, Aniket Chakrabarty

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Field Ridge Segmentation and Navigation Line Coordinate Extraction of Paddy Field Images Based on Machine Vision Fused with GNSS by Muhua Liu, Xulong Wu, Peng Fang, Wenyu Zhang, Xiongfei Chen, Runmao Zhao, Zhaopeng Liu

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Effects of magnesium deficiency on stress manifestations in women of reproductive age with nonspecific vaginitis by O. D. Riazanova, Н. I. Reznichenko

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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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A Next-generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM,... by Tonmoy Deka, Tasneem Basra Khan, Swastik Dewan, Priyankush Ghosh, Debayan Das, Liton Majumdar

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Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis by Lijuan Feng, Kaiyong Bai, Limeng He, Hao Wang, Wei Zhang

“…Additionally, a nomogram model was employed to predict the diagnostic ability of biomarkers for RA. …”
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Estimation of Canopy Chlorophyll Content of Apple Trees Based on UAV Multispectral Remote Sensing Images by Juxia Wang, Yu Zhang, Fei Han, Zhenpeng Shi, Fu Zhao, Fengzi Zhang, Weizheng Pan, Zhiyong Zhang, Qingliang Cui

“…The RF model, which outperforms the other models in terms of the prediction effect in multiple growth stages, can effectively predict the SPAD value in the leaves of apple trees and provide a reference for the growth status monitoring and precise management of orchards.…”
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Machine learning modeling of cancer treatment-related cardiac events in breast cancer: utilizing dosiomics and radiomics by Sefika Dincer, Muge Akmansu, Oya Akyol

“…BackgroundPersonalized medicine has transformed disease management by focusing on individual characteristics, driven by advancements in genome mapping and biomarker discoveries.Objectives:This study aims to develop a predictive model for the early detection of treatment-related cardiac side effects in breast cancer patients by integrating clinical data, high-sensitivity Troponin-T (hs-TropT), radiomics, and dosiomics. …”
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Agenda setting for health equity assessment through the lenses of social determinants of health using machine learning approach: a framework and preliminary pilot study by Maryam Ramezani, Mohammadreza Mobinizadeh, Ahad Bakhtiari, Hamid R. Rabiee, Maryam Ramezani, Hakimeh Mostafavi, Alireza Olyaeemanesh, Ali Akbar Fazaeli, Alireza Atashi, Saharnaz Sazgarnejad, Efat Mohamadi, Amirhossein Takian

“…These models highlighted the importance of features like current health expenditure, domestic general government health expenditure, and GDP in predicting life expectancy. Conclusion The findings underscore the significance of employing innovative methods like CRISP-ML(Q) and ML algorithms to enhance health equity. …”
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The diagnostic and prognostic capability of artificial intelligence in spinal cord injury: A systematic review by Saran Singh Gill, Hariharan Subbiah Ponniah, Sho Giersztein, Rishi Miriyala Anantharaj, Srikar Reddy Namireddy, Joshua Killilea, DanieleS.C. Ramsay, Ahmed Salih, Ahkash Thavarajasingam, Daniel Scurtu, Dragan Jankovic, Salvatore Russo, Andreas Kramer, Santhosh G. Thavarajasingam

“…Results: For prognostication, 11 studies predicted outcomes including AIS improvement (30%), mortality and ambulatory ability (20% each), and discharge or length of stay (10%). …”
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Incorporating food plant distributions as important predictors in the habitat suitability model of sumatran orangutan (Pongo abelii) in Gunung Leuser National Park, Indonesia by Salmah Widyastuti, Wanda Kuswanda, M. Hadi Saputra, Hendra Helmanto, Nunu Anugrah, U. Mamat Rahmat, Rudianto Saragih Napitu, Andrinaldi Adnan, Iskandarrudin

“…This study enhances habitat suitability models (HSM) for Sumatran orangutans by incorporating the predictive distributions for 21 key orangutan food plants, which had not been previously explored. …”
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Membangun Kepercayaan yang Berkelanjutan di Era Disruptif Komunikasi: Perspektif Media dan Komunikasi Digital by Agung Dharmajaya, Harmonis Minangkabawi

“…Transparency, accountability, education and collaboration are important strategies to maintain credibility and trust. …”
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An overview of artificial intelligence based automated diagnosis in paediatric dentistry by Suba B. Rajinikanth, Densingh Samuel Raj Rajkumar, Akshay Rajinikanth, Ponsekar Abraham Anandhapandian, Bhuvaneswarri J.

“…The field of AI, deep machine learning and CNN's is an upcoming and newer area, with new developments this will open up areas for more sophisticated algorithms in multiple layers to predict accurately, when compared to experienced Paediatric dentists.…”
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Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma by Pingfei Tang, Weiming Qu, Dajun Wu, Shihua Chen, Minji Liu, Weishun Chen, Qiongjia Ai, Haijuan Tang, Hongbing Zhou

“…The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm. …”
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Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis. by Shang-Ming Zhou, Fabiola Fernandez-Gutierrez, Jonathan Kennedy, Roxanne Cooksey, Mark Atkinson, Spiros Denaxas, Stefan Siebert, William G Dixon, Terence W O'Neill, Ernest Choy, Cathie Sudlow, UK Biobank Follow-up and Outcomes Group, Sinead Brophy

“…<h4>Objectives</h4>1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs.…”
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Addressing human–elephant conflicts in Taita Taveta County, Kenya: Integrating species distribution modeling into targeted conservation strategies by Tino Johansson, Martha Munyao, Petri K.E. Pellikka, Sakari Äärilä, Patrick Omondi, Mika Siljander

“…This study assesses multiple distribution model algorithms and ensemble models, using Kenya Wildlife Service incident data and ten geospatial variables, to predict human–elephant conflicts in the county. …”
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Big Data Cleaning Based on Improved CLOF and Random Forest for Distribution Networks by Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng

“…First, the Local Outlier Factor (LOF) algorithm based on DBSCAN clustering is used to detect outliers. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…In this study, GPR-based predictive LCA is conducted using historical and real-time environmental data for modeling impact categories of CO2 and energy use. …”
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Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning by Leeran Talker, Cihan Dogan, Daniel Neville, Rui Hen Lim, Henry Broomfield, Gabriel Lambert, Ahmed Selim, Thomas Brown, Laura Wiffen, Julian Carter, Helen F. Ashdown, Gail Hayward, Elango Vijaykumar, Scott T. Weiss, Anoop Chauhan, Ameera X. Patel

“…Output probabilities from the severity determination model produced a correlation of 0.71 with percentage predicted FEV1.Conclusion The N-TidalTM device could be used alongside interpretable machine learning as an accurate, point-of-care diagnostic test for COPD, particularly in primary care as a rapid rule-in or rule-out test. …”
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