💻 Category

cs

2579 papers

💻 computer science

Machine Learning-Based Classification of Epileptic Seizure Activity from EEG Signals: A Comparative Study of Ensemble Methods and Class-Imbalance Mitigation Strategies

This study demonstrates that ensemble machine learning methods, particularly XGBoost and SMOTE-enhanced voting classifiers, achieve high accuracy (up to 98.19%) and improved seizure recall in classifying EEG signals, while also highlighting the critical importance of data integrity through the correction of a dataset provenance error.

Vinayak Pandya, Harshwardhansinh Chauhan, Krushal Gohil, Dharmendra Chavda, Rocky Upadhyay2026-09-26
💻 computer science

Quantifying Data Leakage in Multimodal Clinical Augmentation: A Decomposition Framework and a Leakage-Free Evaluation Protocol for Parkinson's Disease Classification

This paper introduces a decomposition framework and leakage-free evaluation protocol to demonstrate that apparent classification gains from generative augmentation in Parkinson's disease diagnosis are often artifacts of evaluation leakage, revealing that while latent-space balancing produces high-fidelity synthetic data, it fails to improve model performance over unaugmented baselines.

Mohamed Hedi Djemaa, Yohann Chasseray, Rafika Thabet, Farah Jemili, Elyes Lamine2026-09-25
💻 computer science

Multimodal Driver Visual Load Assessment and Prediction under Dynamic Lighting Environments Using RaceGrid-OPTICS and WA-PSRSMformer

This study proposes a multimodal framework that integrates eye-movement, illumination, and vehicle-speed data with a novel RaceGrid-OPTICS clustering algorithm and WA-PSRSMformer deep learning model to accurately assess and predict driver visual load under dynamic lighting conditions, achieving 90.13% accuracy in tunnel environments.

Noman Iqbal, Yishui Zhu, Fenjiao Wang, Luyang Wang2026-09-25
💻 computer science

Occam’s Razor in AI-assisted complex diagnosis: a comparative effectiveness study of single large language models versus multi-agent systems in resource-constrained primary care settings

Contrary to the prevailing assumption that multi-agent systems outperform single models, this study demonstrates that in resource-constrained primary care settings, a single high-performance local LLM (GPT-oss-20b) achieves superior diagnostic accuracy, safety, and latency compared to complex multi-agent architectures, thereby advocating for "Lean AI" strategies over computationally expensive ensemble workflows.

Tengfei Cai, Naiguang Zhang, Yansheng Li, Yanmin Li, Xiaoyan Li, Bo Liu2026-09-25
💻 computer science

A simulation-based framework for sizing paired benchmarks in the evaluation of clinical artificial intelligence, applied to 168 expert-level dyslipidaemia items

This paper presents a simulation-based framework for determining the necessary sample size in paired clinical AI benchmark evaluations to address limitations of traditional methods, demonstrating through a dyslipidaemia study that pre-calculated bank size, rather than system performance alone, dictates whether comparative conclusions are statistically reachable.

Mete Ucdal, Karya Yurtsever, Pınar Yıldız, Ayşen Akalın, Kadir Uğur Mert, Gülay Sain Güven2026-09-25
💻 computer science

MineralBench: an evaluation benchmark of large language models for mineral resources

This paper introduces MineralBench, a comprehensive evaluation benchmark featuring three specialized tasks and four metrics to systematically assess and compare the performance of 13 large language models in the mineral resources domain, revealing significant performance gaps between general and domain-specific capabilities and the task-dependent nature of fine-tuning.

Jiahao Dan, Shengwen Li, Hong Yao, Yuan Cong, Bingyi Li, Hang Zhou2026-09-25
💻 computer science

Design of YOLOv8-SLAM Robot Path Planning Method for Outdoor Complex Environments

This paper proposes an integrated YOLOv8-SLAM framework for outdoor mobile robots that enhances small-target detection, eliminates dynamic interference in visual SLAM, and optimizes global-to-local path planning through a hybrid ant colony and dynamic window approach, resulting in significantly improved perception accuracy, trajectory estimation, and navigation success rates in complex environments.

Zhang Tingting, Xie Qiang2026-09-25
💻 computer science

Knowledge Mapping and Frontier Analysis of Artificial Intelligence Applications in Mental Health Interventions: A CiteSpace‑Based Bibliometric Analysis

This CiteSpace-based bibliometric analysis of 1,685 Web of Science articles reveals a sharp surge in research on AI-driven mental health interventions since 2023, highlighting key contributions from China and the US while identifying current hotspots in large language models and ethical challenges alongside a critical need for standardized clinical translation and multinational collaboration.

Yaxin Xiao, Pan Su, Yujun Lian, Pei Zhou, Lihua Jin2026-09-25