GCNTrack: A Pig-Tracking Method Based on Skeleton Feature Similarity by Zhaoyang Yin, Zehua Wang, Junhua Ye, Suyin Zhou, Aijun Xu

“…This strategy combines IOU matching and skeleton keypoint-based graph convolutional reidentification (Re-ID) algorithms to track pigs continuously, even when pigs return from outside the FOV. …”
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Predicting clozapine-induced adverse drug reaction biomarkers using machine learning by John-Paul Cooper, Pierre Chue, Arno G. Siraki, Lusine Tonoyan

“…Predicting agranulocytosis could improve patient safety. Our study aimed to develop and validate machine learning (ML) models for predicting agranulocytosis in clozapine-prescribed patients using the Canada Vigilance Adverse Reaction Online Database (n = 9395 reports). …”
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Influenza virus genotype to phenotype predictions through machine learning: a systematic review by Laura K. Borkenhagen, Martin W. Allen, Jonathan A. Runstadler

“…We, therefore, offer guidance to overcome these limitations, aid in improving predictive models of previously studied influenza A virus phenotypes, and extend those models to unexplored phenotypes in the ultimate pursuit of tools to enable the characterization of virus isolates across surveillance laboratories.…”
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Predicting emergency department visits for non-traumatic dental-related conditions among Medicaid beneficiaries by Sung Eun Choi, Rindala Fayyad, Daniel Nolte, Christine Riedy, Sharon-Lise Normand

“…We sought to predict future “ED users” for non-traumatic dental-related conditions using machine learning algorithms and identify associated risk factors to help Medicaid outreach programs better target populations in most need of improvement in access to dental care. …”
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Applications of Artificial Intelligence in Vasculitides: A Systematic Review by Mahmud Omar, Reem Agbareia, Mohammad E. Naffaa, Abdulla Watad, Benjamin S. Glicksberg, Girish N. Nadkarni, Eyal Klang

“…Conclusion The current literature shows that AI algorithms can enhance vasculitis diagnosis and prediction, with deep‐ and machine‐learning models showing promise in Kawasaki disease. …”
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Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD by Chenghang Wang, Xiaochun Shen, Zhaoxiang Zhang, Chengyang Tao, Yuelei Xu

“…Finally, a novel dataset, termed the Multi-Information Drone Detection and Tracking Dataset (MIDDTD), is introduced, containing rich drone-related information and diverse scenes, thereby providing a solid foundation for the validation of cross-scene multi-object tracking algorithms. Experimental results demonstrate that the proposed method improves the IDF1 tracking metric by 1.92% compared to existing state-of-the-art methods, showcasing strong cross-scene adaptability and offering an effective solution for multi-object tracking from a drone’s perspective, thereby advancing theoretical and technical support for related fields.…”
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A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques by Rabita Hasan, Sheikh Md. Rabiul Islam

“…A five-fold cross-validation procedure was applied to estimate the model's performance and hyperparameter tuning was conducted to optimize classifier efficiency. …”
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Securing Communication Channels: An Advanced Steganography Approach With Orthogonal Frequency Division Multiplexing (OFDM) by Ammar Mohammedali Fadhil, Ali Y. Jaber

“…In this work, a robust model is proposed to combine OFDM during information hiding. …”
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Optimization of Traffic Flow by Allowing Private Cars to Merge into the Bus Lane at Specific Locations by Zhentao Yin, Kai Yuan, Shenshen Zheng

“…Lane-changing decision is modeled as a result of speed difference between adjacent lanes. …”
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Enhanced water saturation estimation in hydrocarbon reservoirs using machine learning by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Dmitriy A. Martyushev

“…To improve model performance, a Gaussian outlier removal technique was applied to eliminate anomalous data points. …”
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The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce by Jiwang Yin, Xiaodong Qiu, Ya Wang

“…In study 3, based on the SOR theory, we constructed a model and formulated hypotheses and then conducted empirical analysis using 1097 valid questionnaires. …”
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Disseminated intravascular coagulation by Satoshi Gando, Marcel Levi, Cheng-Hock Toh

“…Histones derived from cellular damage play central roles in the innate-immune-based coagulation model, comprising the initiation, amplification, propagation, and reinforcement phases, which, if dysregulated, develop into DIC. …”
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Prediction of the Ultimate Impact Response of Concrete Strengthened with Polyurethane Grout as the Repair Material by Sadi I. Haruna, Yasser E. Ibrahim, Sani I. Abba

“…The SHAP (SHapley Additive exPlanations) analysis showed that the thickness of the grouting materials and maximum load were the most significant parameters affecting the ultimate capacity of the composite U-shaped specimen. The RF model showed moderate improvements, with RF-M3 performing better than RF-M1 and RF-M2. …”
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Machine-learning of medical cannabis chemical profiles reveals analgesia beyond placebo expectations by Adi Hatav, Yelena Vysotski, Anna Shapira, Shiri Procaccia, David Meiri, Dvir Aran

“…We used a Random Forest classifier with nested cross-validation to assess the predictive value of demographics, clinical features, and approximately 200 chemical compounds. Model robustness was evaluated using six additional machine learning algorithms. …”
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GE-YOLO for Weed Detection in Rice Paddy Fields by Zimeng Chen, Baifan Chen, Yi Huang, Zeshun Zhou

“…Therefore, we propose GE-YOLO to identify three common types of weeds in rice fields in the Hunan province of China and to validate its generalization performance. GE-YOLO is an improvement based on the YOLOv8 baseline model. It introduces the Neck network with the Gold-YOLO feature aggregation and distribution network to enhance the network’s ability to fuse multi-scale features and detect weeds of different sizes. …”
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Evaluating Recycling Initiatives for Landfill Diversion in Developing Economies Using Integrated Machine Learning Techniques by Muyiwa Lawrence Adedara, Ridwan Taiwo, Olusola Olaitan Ayeleru, Hans-Rudolf Bork

“…The optimised CatBoost model (accuracy and F1 score of 0.79) identified collection time and the absence of overflowing HSR bins as key motivators for household recycling via the SHapley Additive exPlanations (SHAP) framework. …”
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Diagnostic Analysis of Crosswalk Safety Hazards in Pedestrian Environments: A SHAP-Enhanced Machine Learning Approach With Street-View Imagery by Caryl Anne M. Barquilla, Jeongwoo Lee

“…It used data from 36,750 crosswalks in Seoul, South Korea, to rigorously evaluate multiple machine learning algorithms for predicting pedestrian crash risk. Among the models assessed, the Random forest (RF) demonstrated the highest precision, aligning with the objective of enhancing pedestrian safety through accurate risk identification. …”
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FeCo: Hysteresis, Pseudo-Critical, and Compensation Temperatures on Quasi-Spherical Nanoparticle by Julio Cesar Madera, Elisabeth Restrepo-Parra, Nicolás De La Espriella

“…We investigated the hysteresis, pseudo-critical, and compensation behaviors of a quasi-spherical FeCo alloy nanoparticle (2 nm in diameter) using Monte Carlo simulations with thermal bath-type algorithms and a 3D mixed Ising model. The nanostructure was modeled in a body-centered cubic lattice (BCC) through the following configurations: spin <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mo>=</mo><mn>3</mn><mo>/</mo><mn>2</mn></mrow></semantics></math></inline-formula> for Co and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>Q</mi><mo>=</mo><mn>2</mn></mrow></semantics></math></inline-formula> for Fe. …”
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Personal health data protection and intelligent healthcare applications under generative adversarial network by Xiaoyuan Gao, Wei Mi, Xirui Feng

“…Additionally, the model’s accuracy gradually improves as the privacy budget increases. …”
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Applications of artificial intelligence in neurosurgical education: a scoping review by Hector Julio Piñera-Castro, Christian Borges-García

“…In board examinations, GPT-4 outperformed prior models and junior neurosurgeons in text-based questions but lagged in image-based tasks. …”
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