Individualized Analysis of Nipple‐Sparing Mastectomy Versus Modified Radical Mastectomy Using Deep Learning by Enzhao Zhu, Linmei Zhang, Pu Ai, Jiayi Wang, Chunyu Hu, Huiqing Pan, Weizhong Shi, Ziqin Xu, Yidan Fang, Zisheng Ai

“…Methods To develop treatment recommendations for breast cancer patients, five machine learning models were trained. To mitigate bias in treatment allocation, advanced statistical methods, including propensity score matching (PSM) and inverse probability treatment weighting (IPTW), were applied. …”
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A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience by Umar Islam, Mohammed Naif Alatawi, Ali Alqazzaz, Sulaiman Alamro, Babar Shah, Fernando Moreira

“…Simultaneously, edge computing nodes handle data preprocessing and transmit only valuable information—defined as abnormal or high-risk health signals such as irregular heart rate or oxygen levels—using rule-based filtering, statistical thresholds, and lightweight machine learning models like Decision Trees and One-Class SVMs. …”
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Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control by Denis Pompon, Luis F. Garcia-Alles, Philippe Urban

“…Molecular dynamics was used to characterize subsite interactions and feed a dedicated geometric encoding of trajectories that was coupled to dimensional reductions and differential machine learning. The two subsites differentially control caffeine orientations and can exchange substrate through a phenylalanine gated mechanism. …”
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3D-CNN detection of systemic symptoms induced by different Potexvirus infections in four Nicotiana benthamiana genotypes using leaf hyperspectral imaging by Rizos-Theodoros Chadoulis, Ioannis Livieratos, Ioannis Manakos, Theodore Spanos, Zeinab Marouni, Christos Kalogeropoulos, Constantine Kotropoulos

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Deep unsupervised clustering for prostate auto-segmentation with and without hydrogel spacer by Hengrui Zhao, Biling Wang, Michael Dohopolski, Ti Bai, Steve Jiang, Dan Nguyen

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Topology Unveiled: A New Horizon for Economic and Financial Modeling by Yicheng Wei, Junzo Watada, Zijin Wang

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A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…The experimental results show that the proposed new hybrid model can provide enhanced accuracy with the reduction of prediction error compared with other existing prediction methods.…”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…Currently, more and more intrusion detection systems based on machine learning and deep learning are being applied to SDN, but most have drawbacks such as complex models and low detection accuracy. …”
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Modeling Exhaust Emissions in Older Vehicles in the Era of New Technologies by Maksymilian Mądziel

“…This paper introduces an innovative methodology that takes advantage of advanced AI and machine learning techniques to develop precise emission models for older vehicles. …”
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Predicting Excavation-Induced Tunnel Response by Process-Based Modelling by Linlong Mu, Jianhong Lin, Zhenhao Shi, Xingyu Kang

“…This paper proposes an initiative to solve this problem by using process-based modelling, where information generated from the interaction processes between soils, structures, and excavation activities is utilized to gradually reduce uncertainty related to soil properties and to learn the interaction patterns through machine learning techniques. …”
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Hybrid VLC-RF Channel Estimation for GFDM Wireless Sensor Networks Using Tree-Based Regressor by Azam Isam Aladwani, Tarik Adnan Almohamad, Abdullah Talha Sözer, İsmail Rakıp Karaş

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Intelligent agriculture: deep learning in UAV-based remote sensing imagery for crop diseases and pests detection by Hongyan Zhu, Hongyan Zhu, Chengzhi Lin, Chengzhi Lin, Gengqi Liu, Gengqi Liu, Dani Wang, Dani Wang, Shuai Qin, Shuai Qin, Anjie Li, Anjie Li, Jun-Li Xu, Yong He

“…Additionally, some widely used traditional machine learning (ML) algorithms were presented and the performance results were tabulated to form a comparison. …”
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Enhanced glaucoma detection using U-Net and U-Net+ architectures using deep learning techniques by B.P. Pradeep kumar, Pramod K.B. Rangaiah, Robin Augustine

“…Capsule Networks were utilized for feature extraction and Extreme Learning Machines (ELM) for diagnostic classification. …”
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Accelerating Disease Model Parameter Extraction: An LLM-Based Ranking Approach to Select Initial Studies for Literature Review Automation by Masood Sujau, Masako Wada, Emilie Vallée, Natalie Hillis, Teo Sušnjak

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Medium-Term Hourly Electricity Tariff Forecasting Using Ensemble Models by Matrenin P.V., Arestova A.Yu., Antonenkov D.V.

“…This work aims to study the potential for medium-term forecasting of retail electricity tariff rates and develop a predictive machine learning model. Hourly data on the retail market tariffs of the Novosibirsk region (Siberia) for four years were collected, several machine learning models were applied, and an analysis of the input parameters for forecasting was carried out. …”
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Exploring the thermal attributes of nano-composition (GQDs+Bi2Se3+Ag) suspended in therminol VP-1: An artificial intelligence based approach by Sohail Ahmad, Hessa A. Alsalmah

“…The analysis incorporates a machine learning technique based on recurrent neural network (RNN) to evaluate the nonlinear impacts of the physical parameters. …”
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High risk of political bias in black box emotion inference models by Hubert Plisiecki, Paweł Lenartowicz, Maria Flakus, Artur Pokropek

“…Abstract This paper investigates the presence of political bias in emotion inference models used for sentiment analysis (SA). Machine learning models often reflect biases in their training data, impacting the validity of their outcomes. …”
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Dynamic weighted ensemble model for predictive optimization in green sand casting: Advancing industry 4.0 manufacturing by Rajesh V․ Rajkolhe, Dr. Sanjay S․ Bhagwat, Dr. Priyanka V․ Deshmukh

“…To overcome the limitations of individual machine learning models and static ensemble strategies, a novel Dynamic Weighted Ensemble (DWE) model is introduced. …”
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A Novel Approach for Automatic Detection of Concrete Surface Voids Using Image Texture Analysis and History-Based Adaptive Differential Evolution Optimized Support Vector Machine by Nhat-Duc Hoang, Quoc-Lam Nguyen

“…To improve the productivity of the inspection work, this study develops a hybrid intelligence approach that combines image texture analysis, machine learning, and metaheuristic optimization. …”
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Development of an autoregressive neural network model for predicting accidents in the Khabarovsk Territory by E. V. Shokhirev, P. P. Volodkin, V. A. Lazarev, A. V. Konstantinov

“…The purpose of the study is to compare the actual accident rates in Khabarovsk Krai for the period from 01.01.2015 to 30.11.2023 with the results of the accident prediction model by training and validation based on recurrent neural network using machine learning methods. …”
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