Progression of the first stage of spontaneous labour: A prospective cohort study in two sub-Saharan African countries. by Olufemi T Oladapo, Joao Paulo Souza, Bukola Fawole, Kidza Mugerwa, Gleici Perdoná, Domingos Alves, Hayala Souza, Rodrigo Reis, Livia Oliveira-Ciabati, Alexandre Maiorano, Adesina Akintan, Francis E Alu, Lawal Oyeneyin, Amos Adebayo, Josaphat Byamugisha, Miriam Nakalembe, Hadiza A Idris, Ola Okike, Fernando Althabe, Vanora Hundley, France Donnay, Robert Pattinson, Harshadkumar C Sanghvi, Jen E Jardine, Özge Tunçalp, Joshua P Vogel, Mary Ellen Stanton, Meghan Bohren, Jun Zhang, Tina Lavender, Jerker Liljestrand, Petra Ten Hoope-Bender, Matthews Mathai, Rajiv Bahl, A Metin Gülmezoglu

“…Averaged labour curves may not truly reflect the variability associated with labour progression, and their use for decision-making in labour management should be de-emphasized.…”
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Evaluating User Interactions and Adoption Patterns of Generative AI in Health Care Occupations Using Claude: Cross-Sectional Study by Gabriel Alain, James Crick, Ella Snead, Catherine C Quatman-Yates, Carmen E Quatman

“…Our findings emphasize the urgent need for strategies addressing potential impacts on clinical workflows, patient decision-making, information quality, and health equity. …”
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Improving the Incident Management Process Based on a Use Case Approach by A. A. Mikryukov, A. V. Kuular

“…This method does not require large computational costs and provides the required degree of reliability (error) of the decision. …”
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Automated Distal Radius and Ulna Skeletal Maturity Grading from Hand Radiographs with an Attention Multi-Task Learning Method by Xiaowei Liu, Rulan Wang, Wenting Jiang, Zhaohua Lu, Ningning Chen, Hongfei Wang

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The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials by Vera Malheiro, Beatriz Santos, Ana Figueiras, Filipa Mascarenhas-Melo

“…AI systems work through algorithms based on rules or instructions that enable the machine to make decisions. With the advancement of science, more sophisticated AI techniques, such as machine learning and deep learning, have been developed, allowing machines to learn from large amounts of data and improve their performance over time. …”
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Gated-LNN: Gated Liquid Neural Networks for Accurate Water Quality Index Prediction and Classification by Sreeni Chadalavada, Suleyman Yaman, Abdulkadir Sengur, Abdul Hafeez-Baig, Ru-San Tan, Prabal Datta Barua, Ravinesh C. Deo, Makiko Kobayashi, U. Rajendra Acharya

“…Recent advances in machine learning (ML) have brought new approaches to predicting water quality index (WQI) and classifying water quality in real time to enhance decision-making in environmental management. In this study, we propose a novel gated liquid neural network (gated-LNN) that can predict WQI and classify water quality with high accuracy. …”
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On using dynamical seasonal forecasts to develop management-driven wildland fire outlooks in Alaska by Cecilia Borries-Strigle, Uma S. Bhatt, Peter A. Bieniek, Mitchell Burgard, Eric Stevens, Heidi Strader, Richard L. Thoman, Alison York, Robert H. Ziel

“…Throughout this work, we have taken an operational perspective, aiming to keep methods computationally efficient to accommodate the large data volumes and time-sensitive decision-making. …”
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Awareness program for controlling the misuse of antibiotics and related resistance among mothers of children under 5 years by Zainab Attia Abdallah, Tanazor Hemdan Abdel Hamid, Sameh S. Zaghlool, Abdelaziz Hendy, Khalid Al-Mugheed, Sally Mohammed Farghaly Abdelaliem, Amany Anwar Saeed Alabdullah, Salwa Sayed, Ahmed Hendy, Ayiat Allah Wagdy Farag

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Aqua-MC as a simple open access code for uncountable runs of AquaCrop by Vahid Adabi, Hadi Ramezani Etedali, Asghar Azizian, Faraz Gorginpaveh, Ali Salem, Ahmed Elbeltagi

“…Abstract Understanding uncertainty in crop modeling is essential for improving prediction accuracy and decision-making in agricultural management. Monte Carlo simulations are widely used for uncertainty and sensitivity analysis, but their application to closed-source models like AquaCrop presents significant challenges due to the lack of direct access to source code. …”
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Segmentation and finite element analysis in orthopaedic trauma by Kevin Y. Wang, Alexander R. Farid, Simon Comtesse, Arvind G. von Keudell

“…It plays a pivotal role in predicting fracture risk, assessing construct stability, and informing surgical decision-making. …”
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Stratified Multisource Optical Coherence Tomography Integration and Cross-Pathology Validation Framework for Automated Retinal Diagnostics by Michael Sher, Riah Sharma, David Remyes, Daniel Nasef, Demarcus Nasef, Milan Toma

“…The methodology integrates biomimetic data partitioning, deep biomarker extraction via pretrained VGG16 networks, and automated model selection optimized for clinical decision-making. Stratified data curation preserved pathological distributions across training, validation, and testing subsets, while SMOTE optimization mitigated class imbalance. …”
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Research advances in evaluation methods for neoadjuvant therapy of tumors by Zien Yuan, Ting Chen, He Zhang, Jiatong Li, Juntan Li, Guanning Shang

“…The Miller–Payne criteria focus on changes in the number and density of tumor cells and provide a reference for surgical decision-making. Nevertheless, it does not consider lymph node metastasis. …”
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Pooled prevalence and determinants of household satisfaction with the community-based health insurance (CBHI) scheme in Ethiopia: a systematic review and meta-analysis by Getasew Berhanu, Yodit Abebe, Gizaw Sisay, Kassahun Animut

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Optimisation of the deployment of automated external defibrillators in public places in England by Terry P Brown, Lazaros Andronis, Asmaa El-Banna, Benjamin KH Leung, Theodoros Arvanitis, Charles Deakin, Aloysius N Siriwardena, John Long, Gareth Clegg, Steven Brooks, Timothy CY Chan, Steve Irving, Louise Walker, Craig Mortimer, Sandra Igbodo, Gavin D Perkins

“…For the cost-effectiveness analysis a de novo decision-analytic model was developed and used as a vehicle for assessing the costs and benefits of deployment strategies at POIs compared to current AED placement. …”
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Patellar Non-Traumatic Pathologies: A Pictorial Review of Radiologic Findings by Zahra Masroori, Sara Haseli, Elahe Abbaspour, Alireza Pouramini, Arash Azhideh, Marjan Fathi, Fatemeh Kafi, Majid Chalian

“…Furthermore, this review highlights specific radiologic features for a range of non-traumatic patellar conditions, including patellar tendinopathy, chondromalacia patellae, and trochlear dysplasia, emphasizing how distinct radiologic findings facilitate precise diagnosis and clinical assessment. Ultimately, it provides a practical guide for clinicians in diagnosing non-traumatic patellar pathologies through a comprehensive review of key radiologic features while also discussing advancements in imaging technologies and management strategies to support accurate diagnosis and effective clinical decision-making.…”
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Modeling Temperature and Moisture Dynamics in Corn Storage Silos: A Comparative 2D and 3D Approach by Fernando Iván Molina-Herrera, Luis Isai Quemada-Villagómez, Mario Calderón-Ramírez, Gloria María Martínez-González, Hugo Jiménez-Islas

“…The 2D model offers computational efficiency and is suitable for preliminary assessments but simplifies natural convection effects and underestimates axial temperature gradients. …”
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Application of Artificial Neural Networks to Predict the Use of Mobile Learning by University Students by Alejandro Valencia-Arias, Julián Alberto Uribe-Gómez, Evelyn Flores-Siapo, Lucia Palacios-Moya, Ada Gallegos, Ezequiel Martínez Rojas

“…ANNs are supervised machine learning techniques that imitate the organization and operation of the human brain to process data and render decisions. ANNs are computer systems that can learn from observation and experience, much like the human brain, and can subsequently use the acquired knowledge to recognize patterns and make predictions. …”
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ExAutoGP: Enhancing Genomic Prediction Stability and Interpretability with Automated Machine Learning and SHAP by Yao Rao, Lilian Zhang, Lutao Gao, Shuran Wang, Linnan Yang

“…All models were trained and evaluated using five repeated five-fold cross-validation, and their performance was assessed based on both predictive accuracy and computational efficiency. …”
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Artificial intelligence-driven classification method of grapevine major phenological stages using conventional RGB imaging by Ruben Íñiguez, Fikile Wolela, María Ignacia Gonzalez Pavez, Ignacio Barrio, Javier Tardáguila, Talitha Venter, Carlos Poblete-Echeverria

“…Despite these challenges, the study confirms that AI models can effectively automate vineyard phenology classification, reducing manual assessment efforts, and contributing to more efficient viticultural decision-making. …”
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Augmented Reality for Identifying Maintainability Concerns during Design by Imad A. Khalek, Jad M. Chalhoub, Steven K. Ayer

“…Student participants, without prior maintenance experience, were randomly assigned to explore a design to assess maintainability concerns with either augmented reality (AR) or a traditional computer screen for viewing a Building Information Model (BIM). …”
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