Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…Grid search five-fold cross-validation was employed for comprehensive hyperparameter optimization, in conjunction with balanced sampling techniques. …”
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Design of Morlet wavelet neural networks integrated with sequential quadratic programming to analyze the dynamics of Ebola virus disease by Asifa Ashraf, Abaid Ur Rehman Virk, Umar Ishtiaq, Ahmed Samy Mohamed Elwahsh, Ioan-Lucian Popa

“…For the investigation of this model, we use a hybrid optimization algorithm with MWNNs and a genetic algorithm (GA) integrated with sequential quadratic programming (SQP). …”
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Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

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Location Problem - Routing a vehicle with a specified fuel capacity based on a tough time window and customer satisfaction by Mohammad Moshrefi

“…In this research, first, a mixed integer linear programming model is presented and then metaheuristic method based on Non-dominated Sorting Genetic Algorithm is proposed to find the optimal solution. …”
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Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach by Marko Martinović, Kristian Dokic, Dalibor Pudić

“…Logistic regression proved to be the most computationally efficient model despite its weaker predictive power. …”
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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

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Angle detection method for surface mount components based on weighted clustering by Chunfu ZHANG, Zhiqiang SONG

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Game Interactive Learning: A New Paradigm towards Intelligent Decision-Making by Junliang Xing, Zhe Wu, Zhaoke Yu, Renye Yan, Zhipeng Ji, Pin Tao, Yuanchun Shi

“…The proposed paradigm first inherits methods in game theory to model the agents and their preferences in the complex decision-making process. It then optimizes the learning objectives from equilibrium analysis using reformed machine learning algorithms to compute and pursue promising decision results for practice. …”
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An ensemble time-embedded transformer model for traffic conflict prediction at RRFB pedestrian crossings by Md Jamil Ahsan, Mohamed Abdel-Aty, B M Tazbiul Hassan Anik, Zubayer Islam

“…Fifty-two hours of video data were collected using portable CCTV cameras and analyzed using computer vision algorithms. A bounding box system was employed to predict vehicle conflict points and collision pairs. …”
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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Traditional sensor-based techniques such as CO₂ concentration monitoring, passive infrared (PIR) sensors, radio frequency (RF) signals, and indirectly, smart meter data are examined alongside more innovative, vision-based approaches incorporating deep learning and computer vision. Particular attention is paid to data-driven methods, including probabilistic models such as Hidden Markov Models (HMMs), classical machine learning algorithms such as Support Vector Machines (SVMs) and K-Nearest Neighbors (KNN), and deep learning architectures such as Convolutional Neural Networks (CNNs), all of which have demonstrated high accuracy in both laboratory and real-world settings. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

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Synergistic Hierarchical AI Framework for USV Navigation: Closing the Loop Between Swin-Transformer Perception, T-ASTAR Planning, and Energy-Aware TD3 Control by Haonan Ye, Hongjun Tian, Qingyun Wu, Yihong Xue, Jiayu Xiao, Guijie Liu, Yang Xiong

“…The framework integrates (1) a novel adaptation of the Swin-Transformer to generate a dense, semantic risk map from raw visual data, enabling the system to interpret ambiguous marine conditions like sun glare and choppy water, enabling real-time environmental understanding crucial for guidance; (2) a Transformer-enhanced A-star (T-ASTAR) algorithm with spatio-temporal attentional guidance to generate globally near-optimal and energy-aware static paths; (3) a domain-adapted TD3 agent featuring a novel energy-aware reward function that optimizes for USV hydrodynamic constraints, making it suitable for long-endurance missions tailored for USVs to perform dynamic local path optimization and real-time obstacle avoidance, forming a key control element; and (4) CUDA acceleration to meet the computational demands of real-time ocean engineering applications. …”
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Classification of left and right-hand motor imagery in acute stroke patients using EEG microstate by Shiyang Lv, Xiangying Ran, Mengsheng Xia, Yehong Zhang, Ting Pang, Xuezhi Zhou, Zongya Zhao, Yi Yu, Zhixian Gao

“…Abstract Background Stroke is one of the leading causes of adult disability, often resulting in motor dysfunction and brain network reorganization. Brain-computer interface (BCI) systems offer a novel approach to post-stroke motor rehabilitation, with motor imagery (MI) serving as a key paradigm that requires decoding left and right-hand MI differences to optimize system performance. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…The fusion of Artificial intelligence (AI) with computational chemistry has revolutionized drug discovery by enhancing compound optimization, predictive analytics, and molecular modeling. …”
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Enhancing medical response efficiency in real-time large crowd environments via smart coverage and deep learning for stable ecological health monitoring by Asma A. Alhashmi, Ghada Moh. Samir Elhessewi, Mukhtar Ghaleb, Nazir Ahmad, Nojood O. Aljehane, Tareq M. Alkhaldi, Hamad Almansour, Samah Al Zanin

“…The primary objective of this paper is to propose an effective method for enhancing medical response efficiency in large crowd environments by utilizing advanced optimization algorithms. Initially, the MRELC-SCHO model utilizes min-max normalization to transform the input data into a structured format. …”
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Minimization of Construction and Operation Costs of the Fuel Cell Bus Transportation System by Po-Han Chiang, Bwo-Ren Ke, Shi-Jim Yen, Wei-Che Chien

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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The priors are constructed using cosine similarity, mean, and intensity, where intensity is computed using the improved Papoulis–Gerchberg algorithm. …”
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WebShield 5.0: Harnessing AI and NLP to combat web threats in Industry 5.0 by Priyanka Verma, Donna O’Shea, Thomas Newe, Ankit Vidyarthi, Deepak Gupta, Jabir Ali, Hamad Aldawsari, John G. Breslin

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Beyond the Current Curve: A Novel Curve Warning System Considering Subsequent Curve Speed Limits by N. S. Manikandan, Ganesan Kaliyaperumal

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Research on Collaborative Delivery Path Planning for Trucks and Drones in Parcel Delivery by Ting Fu, Sheng Li, Zhi Li

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