Predicting postpartum female sexual interest/arousal disorder via adiponectin and biopsychosocial factors: a cohort-based decision tree study by Saiedeh Sadat Hajimirzaie, Najmeh Tehranian, Amin Golabpour, Ahmad Khosravi, Seyed Abbas Mousavi, Afsaneh Keramat, Mehdi Mirzaii

“…To better diagnose individuals at risk of postpartum complications, predictive models utilizing data mining and machine learning techniques can be instrumental. The C4.5 decision tree algorithm effectively analyzes multiple variables to identify key relationships. …”
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Barriers and enablers of using a clinical decision support algorithm to consult sick children at primary health facilities: A qualitative study from Uttar Pradesh, India by Mansi Tyagi, Divas Kumar, Kovid Sharma, Fenella Beynon, Gaurav Kumar, Hélène Langet, Gillian A. Levine, Michael A. Ruffo, Mira Emmanuel Fabula, Valérie D'Acremont, Kaspar Wyss, Leah F. Bohle, Shally Awasthi

“…Objective was to explore barriers and enablers experienced by HCPs using a digital clinical decision support algorithm (CDSA) for consultation of sick under-five children at primary healthcare facilities in Uttar Pradesh, India. …”
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MSCSO: A Modified Sand Cat Swarm Algorithm for 3D UAV Path Planning in Complex Environments with Multiple Threats by Zhengsheng Zhan, Dangyue Lai, Canjian Huang, Zhixiang Zhang, Yongle Deng, Jian Yang

“…To improve the global search efficiency and dynamic adaptability of the Sand Cat Swarm Optimization (SCSO) algorithm for UAV path planning in complex 3D environments, this study proposes a Modified Sand Cat Swarm Optimization (MSCSO) algorithm by integrating chaotic mapping initialization, Lévy flight–Metropolis hybrid exploration mechanisms, simulated annealing–particle swarm hybrid exploitation strategies, and elite mutation techniques. …”
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Enhancing clinical decision-making: a scenario-based patient simulation study using QR code-based algorithms for the management of acute intoxication-type inborn errors of metaboli... by Merve Koç Yekedüz, Gülçin Bilicen Yarenci, Muhammet Taş, Nilüfer Okur, Fatma Tuba Eminoğlu

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Multi-Biometric Feature Extraction from Multiple Pose Estimation Algorithms for Cross-View Gait Recognition by Ausrukona Ray, Md. Zasim Uddin, Kamrul Hasan, Zinat Rahman Melody, Prodip Kumar Sarker, Md Atiqur Rahman Ahad

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Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cas... by Hidde Dijkstra, Cathleen S Parsons, Hanne-Eva VAN Bremen, Hanna C Willems, Anne A H De Hond, Barbara C van Munster, Job N Doornberg, Jacobien H F Oosterhoff

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Design and Optimization of Hybrid CNN-DT Model-Based Network Intrusion Detection Algorithm Using Deep Reinforcement Learning by Lu Qiu, Zhiping Xu, Lixiong Lin, Jiachun Zheng, Jiahui Su

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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

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Modeling and Optimization of Tensile Properties of Epoxy Biocomposites Reinforced with Washingtonia robusta Waste and Biochar Using Response Surface Methodology, Artificial Neural... by Messaouda Boumaaza, Ahmed Belaadi, Hassan Alshahrani, Ibrahim M. H. Alshaikh, Djamel Ghernaout

“…Optimization results indicated ideal conditions of 29.35–29.41% WRW, 11.06–11.24 h treatment time, and 2.99–3% NaOH, based on desirability function RSM and genetic algorithm ANN optimization. …”
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Deep reinforcement learning for conservation decisions by Marcus Lapeyrolerie, Melissa S. Chapman, Kari E. A. Norman, Carl Boettiger

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Bone reporting and data system on CT (Bone-RADS-CT): a validation study by four readers on 328 cases from three local and two public databases by Yue Xing, Defang Ding, Shun Dai, Yangfan Hu, Xianwei Liu, Liangjing Lyu, Guangcheng Zhang, Shiqi Mao, Qian Yin, Junjie Lu, Jiarui Yang, Yang Song, Huan Zhang, Chengzhou Li, Weiwu Yao, Jingyu Zhong

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Bone Reporting and Data System on MRI (Bone-RADS-MRI): a validation study by four readers on 275 cases from three local and two public databases by Yue Xing, Yangfan Hu, Xianwei Liu, Defang Ding, Shun Dai, Liangjing Lyu, Guangcheng Zhang, Shiqi Mao, Qian Yin, Junjie Lu, Jiarui Yang, Yang Song, Huan Zhang, Chengzhou Li, Weiwu Yao, Jingyu Zhong

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Intelligent implementation of muscle strain identification algorithm in Mi health exercise induced waist muscle strain by Hu Wei, Zhong Hao, Wang Changyong

“…In order to improve the accuracy and efficiency of identifying lumbar muscle strain, based on the You Only Look Once version 3 algorithm, an intelligent recognition filtering algorithm combining sliding window and histogram of oriented gradient features is proposed to avoid misdiagnosis caused by artifact interference. …”
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Diagnostic performance of a new algorithm combining simple, non-invasive and inexpensive tests for predicting the presence of advanced liver fibrosis in patients with chronic hepat... by Jean Nana, Jean Luc Bosson, Kristina Skaare, Céline Vermorel, Vincent Leroy, Tarik Asselah, Michael Adler, Jean-Pierre Zarski

“…Results A total of 408 patients were used to develop a decision tree algorithm, which established Decision Rule No. 1 for predicting the risk of advanced fibrosis (F3-F4): if platelets < 185 × 109/L and age ≥ 38 years and GGT ≥ 27 IU/L, then the patient is classified as F3-F4. …”
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Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm by Anjan Kumar, Laith Hussein Jasim, Padmanabha Vijaya, Dipak Patel, J. Gowrishankar, R. Sivaranjani, Ankur Srivastava, Mayank Kundlas, Sarbeswara Hota, Banafshe Hamidi

“…In the first phase, predictive modeling was performed using multilayer perceptron neural networks (MLPNN) optimized by three metaheuristic algorithms: cheetah optimizer (CO), grey wolf optimizer (GWO), and marine predators algorithm (MPA). …”
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Decision Fusion System for Bolted Joint Monitoring by Dong Liang, Shen-fang Yuan

“…Then, a developed decision fusion system is presented. Finally, three fusion algorithms, which consist of majority voting, Bayesian belief, and multiagent method, are adopted for comparison in a real-world monitoring experiment for the large aviation aluminum plate. …”
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Evidence and reality: an observational study on pharmacological outcomes in advanced head and neck tumors by Consuelo Jordán de Luna, Consuelo Jordán de Luna, Anna Esteve, Olalla Montero Pérez, Ana Clopés Estela, Ana Clopés Estela, Marc Oliva, Alicia Lozano Borbalas, Ricard Mesía Nin

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Correction: Evidence and reality: an observational study on pharmacological outcomes in advanced head and neck tumors by Consuelo Jordán de Luna, Consuelo Jordán de Luna, Anna Esteve, Olalla Montero Pérez, Ana Clopés Estela, Ana Clopés Estela, Marc Oliva, Alicia Lozano Borbalas, Ricard Mesía Nin

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Differential Diagnosis of Jejunum and Ileum Tumours Based on Video Capsule Endoscopy Data Using Mathematical Analysis by E. D. Fedorov, E. V. Ivanova, S. E. Rauzina, D. E. Seleznev, A. V. Budykina

“…The developed diagnostic algorithm can support decision making by the clinician within the task of differentiating jejunum or ileum tumour lesions into three main types: benign epithelial tumours, benign non-epithelial tumours and malignant tumours. …”
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Effectiveness of introducing pulse oximetry and clinical decision support algorithms for the management of sick children in primary care in Kenya and Senegal on referral and antibi... by Hélène Langet, Papa Moctar Faye, Francis Njiri, Silvia Cicconi, Gillian A. Levine, Tracy R. Glass, Rose J. Kosgei, Kevin Ngari, Fabian Schaer, Aliou Thiongane, Jean Augustin Diégane Tine, Maymouna Ba, Leah F. Bohle, Mira Emmanuel-Fabula, Mouhamadou Mansour Faye, Susan Horton, Andolo Miheso, Mercy Mugo, Mariah Ngutu, Michael Ruffo, Janet Shauri, Ndèye Marème Sougou, Valérie D’Acremont, Kaspar Wyss, Ousmane Ndiaye, Fenella Beynon

“…Pulse oximetry and digital Clinical Decision Support Algorithms (CDSAs) can strengthen the detection and management of severe childhood illnesses, and support antibiotic stewardship in primary care, but lack evidence for scale-up. …”
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