Exploring the application of machine learning and SHAP explanations to predict health facility deliveries in Somalia by Jamilu Sani, Salad Halane, Mohamed Mustaf Ahmed, Abdiwali Mohamed Ahmed, Jamal Hassan Mohamoud

“…Methods This study analyzed data from the 2020 Somalia Demographic and Health Survey (SDHS) involving 8,951 women aged 15–49 years. Seven ML algorithms, Random Forest, XGBoost, Gradient Boosting, Logistic Regression, Support Vector Machine, Decision Tree, and K-Nearest Neighbors, were evaluated for their ability to predict health facility deliveries. …”
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Machine-Learning-Based Classification of Electronic Devices Using an IoT Smart Meter by Paulo Eugênio da Costa Filho, Leonardo Augusto de Aquino Marques, Israel da S. Felix de Lima, Ewerton Leandro de Sousa, Márcio Eduardo Kreutz, Augusto V. Neto, Eduardo Nogueira Cunha, Dario Vieira

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An Interpretable Machine Learning Model Based on Inflammatory–Nutritional Biomarkers for Predicting Metachronous Liver Metastases After Colorectal Cancer Surgery by Hao Zhu, Danyang Shen, Xiaojie Gan, Ding Sun

“…<b>Methods</b>: This study enrolled 680 patients with CRC who underwent curative resection, randomly allocated into a training set (n = 477) and a validation set (n = 203) in a 7:3 ratio. Feature selection was performed using Boruta and Lasso algorithms, identifying nine core prognostic factors through variable intersection. …”
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Transforming Manufacturing Quality Management with Cognitive Twins: A Data-Driven, Predictive Approach to Real-Time Optimization of Quality by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…By utilizing the power of machine learning algorithms, the cognitive twin constantly monitors and then analyzes real-time data. …”
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Assessing the Level of Understanding (Knowledge) and Awareness of Diagnostic Imaging Students in Ghana on Artificial Intelligence and Its Applications in Medical Imaging by James William Ampofo, Christian Ven Emery, Ishmael Nii Ofori

“…Medical imaging has benefited from AI by reducing radiation risks through algorithms used in examinations, referral protocols, and scan justification. …”
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Digital Academic Leadership in Higher Education Institutions: A Bibliometric Review Based on CiteSpace by Olaniyi Joshua Olabiyi, Carl Jansen van Vuuren, Marieta Du Plessis, Yujie Xue, Chang Zhu

“…Using CiteSpace software (version 6.3. R1-64 bit), we analyzed 5837 documents, identifying 24 key publications that formed a network of 90 nodes and 256 links. …”
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Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi... by Viswanathan Baskar, Mani Arun Vignesh, Sumanth C Raman, Arun Jijo, Bhavadharini Balaji, Nico Steckhan, Lena Maria Klara Roth, Moneeza K Siddiqui, Saravanan Jebarani, Ranjit Unnikrishnan, Viswanathan Mohan, Ranjit Mohan Anjana

“…Its performance was compared with an algorithm determined based on conditional pre-determined cut-offs and weights for each clinical feature [age at diagnosis, BMI, waist, HbA1c, Serum Triglycerides, HDL-Cholesterol, (C-peptide fasting, C-peptide stimulated) - optional. …”
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Innovative cone resistance and sleeve friction prediction from geophysics based on a coupled geo-statistical and machine learning process by A. Bolève, R. Eddies, M. Staring, Y. Benboudiaf, H. Pournaki, M. Nepveaux

“…However, local, in situ 1D measurements can fail to capture 3D subsurface variations, which could mean less than optimal design decisions for foundation engineering. …”
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Prediction of recurrence after surgery for pituitary adenoma using machine learning- based models: systematic review and meta-analysis by Ibrahim Mohammadzadeh, Bardia Hajikarimloo, Behnaz Niroomand, Nasira Faizi, Pooya Eini, Mohammad Amin Habibi, Alireza Mohseni, Mohammadmahdi Sabahi, Abdulrahman Albakr, Michael Karsy, Hamid Borghei-Razavi

“…For the comparison between Logistic Regression (LR) and non-LR algorithms, LR-based algorithms exhibited numerically higher AUC and sensitivity; however, these differences were not statistically significant. …”
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Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

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Performance prediction of radio frequency based negative ion source using fusion neural network model by Yu Gu, Chundong Hu, Yang Li, Yuwen Yang, Yahong Xie, Qinglong Cui, Yuanzhe Zhao

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The 2024 revised clinical guidelines on the management of thyroid tumors by the Japan Association of Endocrine Surgery by Iwao Sugitani, Naomi Kiyota, Yasuhiro Ito, Naoyoshi Onoda, Tomo Hiromasa, Kiyomi Horiuchi, Seigo Kinuya, Tetsuo Kondo, Sueyoshi Moritani, Kiminori Sugino, Hisato Hara

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Recent Advances in Demand Responsive Transport: Opportunities With Autonomous Bus Service&#x2014;A System-of-Systems Overview by Sajid Fadlelseed, Pouria Sarhadi, Soodamani Ramalingam, Hock C. Gan, Pandelis Kourtessis, Gav Jackman, Atziri Guadalupe Sanchez Contreras, Javier Guimera Tena, James West, Jack Holland, Alice Missler

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A model to simulate human cardio-respiratory responses to different fluid resuscitation treatments after hemorrhagic injury by Varghese Kurian, Varghese Kurian, Xin Jin, Xin Jin, Sridevi Nagaraja, Sridevi Nagaraja, Anders Wallqvist, Jaques Reifman

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Machine learning-based prediction of scale formation in produced water as a tool for environmental monitoring by Arash Tayyebi, Ali Alshami, Erfan Tayyebi, Ademola Owoade, MusabbirJahan Talukder, Nadhem Ismail, Zeinab Rabiei, Xue Yu, Glavic Tikeri

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GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

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Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update by Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari

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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning by Jan Li, Tim Coopmans, Patrick Emonts, Kenneth Goodenough, Jordi Tura, Evert van Nieuwenburg

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Revolutionizing FANETs With Reinforcement Learning: Optimized Data Forwarding and Real-Time Adaptability by Yasir Ibraheem Mohammed, Rosilah Hassan, Mohammad Kamrul Hasan, Shayla Islam, Huda Saleh Abbas, Muhammad Asghar Khan, Muhammad Attique Khan

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Population Cohort-Validated PM_2.5-Induced Gene Signatures: A Machine Learning Approach to Individual Exposure Prediction by Yu-Chung Wei, Wen-Chi Cheng, Pinpin Lin, Zhi-Yao Zhang, Chi-Hsien Chen, Chih-Da Wu, Yue Leon Guo, Hung-Jung Wang

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