Design of a dynamic trust management and defense decision system for shared vehicle data based on blockchain and deep reinforcement learning by Jinxiang Chen, Yan Li, Jiaxing Deng, Beicheng Qin, Chengcai He, Qiangsheng Huang, Jingchun Wu

“…The DQN-based system achieves a performance increase exceeding 20% compared to Q-learning, highlighting its decision-making efficacy. (3) Malicious Behavior Detection Rate: Measures the system’s ability to detect and address malicious activities. …”
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Performance of an ultrasound diagnostic algorithm for acute dyspneic patients in the emergency department: an EMERALD-US protocol by Adrien Bassand, Tahar Chouihed, Nicolas Girerd, Xavier Lepage, Ludovic Merckle, Anthony Chauvin, Aurélien Buessler, Deborah Jaeger, Kevin Duarte, Charlene Duchanois, Jérôme Bokobza, Alice Penine, Gaetan Giacomin, Cyrielle Brossard

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Cost-effectiveness of follow-up algorithms for chronic thromboembolic pulmonary hypertension in pulmonary embolism survivors by Dieuwke Luijten, Wilbert B. van den Hout, Gudula J.A.M. Boon, Stefano Barco, Harm Jan Bogaard, Marion Delcroix, Karl-Friedrich Kreitner, Matthias Held, Menno V. Huisman, Luis Jara-Palomares, Stavros V. Konstantinides, Lucia J.M. Kroft, Albert T.A. Mairuhu, Lilian J. Meijboom, Thijs E. van Mens, Maarten K. Ninaber, Esther J. Nossent, Piotr Pruszczyk, Luca Valerio, Anton Vonk Noordegraaf, Frederikus A. Klok

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Evaluation of three commercial rapid immunoassays for the diagnosis of Clostridioides difficile infection by Hannes Bjarki Vigfússon, Theresa Ennefors, Torbjörn Norén, Martin Sundqvist

“…Several commercial rapid immunoassays that detect both GDH and toxin A/B in stool samples are available and could be used for both steps of the diagnostic algorithm. We aimed to evaluate the performance of three of these rapid immunoassays and study pathogen characteristics that might affect the sensitivity of toxin A/B detection. …”
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GLOPS: A Hybrid Approach for Enhanced Scheduling in Cloud Computing Environments via Machine Learning-Based Process Prediction by Syed Abu Ammar Muhammad Zarif, Layla Kader Suma, Md. Sadat Rahman, Md. Motaharul Islam, Phuoc Hung Pham, Phong Dung Thi Nguyen, Nguyen Thanh Binh

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Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qualitative study of healthcare professionals’ perspectives in the UK by Saoudi CE Nouis, Victoria Uren, Srushti Jariwala

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Improved AODV route recovery in mobile ad-hoc networks using a genetic algorithm by Ahmad Maleki, Mehdi Sadeghzadeh

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Reputation-Enhanced Practical Byzantine Fault Tolerance Algorithm for Node Capture Attacks on UAV Networks by Peter Onukak, Simeon Ogunbunmi, Yu Chen, Erika Ardiles-Cruz, Erik Blasch, Genshe Chen

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A Machine Learning Algorithm for Supplier Credit Risk Assessment Based on Supply Chain Management by Yuqian Wei

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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images by Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar

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Predicting major amputation risk in diabetic foot ulcers using comparative machine learning models for enhanced clinical decision-making by Zixuan Liu, Dehua Wei, Jiangning Wang, Lei Gao

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Remote clinical decision support tool for Parkinson’s disease assessment using a novel approach that combines AI and clinical knowledge by Harel Rom, Ori Peleg, Yovel Rom, Anat Mirelman, Gaddi Blumrosen, Inbal Maidan

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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

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Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models by Hongxia Ma, Jiandong Liu, Jia Zhang, Jiandong Huang

“…The beetle antennae search (BAS) algorithm was employed to tune the hyperparameters of the developed machine learning models. …”
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Research on an Efficient Network Advanced Orbiting Systems Comprehensive Multiplexing Algorithm Based on Elastic Time Slots by Haowen Zhu, Zhen Zhang, Zhen Li, Jinwei Cheng, Zhonghe Jin

“…The AOS network traffic is categorized into three types based on its characteristics, and a strongly scalable AOS integrated multiplexing model is established, which consists of a packet multiplexing layer, a virtual channel multiplexing layer, and a decision-making layer. …”
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ANALYZING THE EFFECT OF SIMILARITY FUNCTIONS ON PARTITIONING AROUND MEDOIDS ALGORITHM FOR MAPPING DHF DISEASE IN NORTH SUMATRA by Wahyu Nur Fadillah, Yulita Molliq Rangkuti, Ichwanul Muslim Karo Karo

“…North Sumatra is among the three provinces with the highest incidence and mortality rates in Indonesia. …”
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Use of X means and C4.5 algorithms on lateral cephalometric measurements to identify craniofacial patterns by Merve Gonca, Mehmet Birol Özel

“…Results A total of four clusters were obtained using the X-means algorithm. Decision trees were used to identify the most discriminative variables among clusters. …”
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Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city by Xuechun Zhou, Xiaofei Zou, Wenzuixiong Xiong

“…Core indicators were integrated from three dimensions: residents' health, environmental quality, and community interaction. …”
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A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…This paper proposes a novel prescriptive analytics approach based on Fuzzy Cognitive Maps (FCMs) integrated with Genetic Algorithms (GAs) to support decision-making in the treatment of common cattle diseases. …”
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RACER: A Lightweight Distributed Consensus Algorithm for the IoT with Peer-Assisted Latency-Aware Traffic Optimisation by Zachary Auhl, Harsha Moraliyage, Naveen Chilamkurti, Damminda Alahakoon

“…Recent research has identified three common limitations in existing consensus mechanisms for IoT environments: dependence on synchronised networks and clocks, reliance on centralised coordinators, and suboptimal performance. …”
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