💻 Category

cs

3020 papers

💻 computer science

Implementation and Study on Liver Cirrhosis Disease Diagnosis Prediction Using a Method for Machine Learning Algorithms: A Comparative Approach Analysis

This paper presents a comparative analysis of machine learning algorithms applied to anonymized clinical records from the 'Aadarshvelu' dataset, demonstrating that a proposed labeled attention model achieves superior diagnostic accuracy (94.05%) and F1 score (95.05%) for predicting liver cirrhosis stages, thereby offering a cost-effective tool to enhance early detection and clinical decision-making.

Rajani Kumari, Daya Shankar Singh2026-07-08
💻 computer science

SPIDER-WEB enables a real-time data retrieval of DNA-based data storage

The paper introduces SPIDER-WEB, an all-in-one coding framework that enables real-time, concurrent data retrieval during DNA sequencing, achieving efficiency gains of up to 9,083-fold over conventional methods and demonstrating compact-disc-level performance with successful video rendering in under 100 seconds.

Yue Shen, Haoling Zhang, Xiaoyi Lin, Zhaojun Lan, Demin Xu, Yun Wang, Ziqing Deng, Wen Wang, Jesper Tegner, Xun Xu, Zhi (…)2026-07-08
💻 computer science

Proactive Defence in IoT Networks: A Scoping Review of Security Frameworks and Key Security Elements in Digital Health Systems

This scoping review analyzes existing IoT security frameworks for digital health systems, revealing that while current solutions often address discrete areas, they lack comprehensive integration, and it identifies key elements like vulnerability assessments, threat modelling, and AI as essential for developing robust, proactive defense mechanisms.

Gihan Gunasekara, Patricia A.H. Williams, Ginger Mudd2026-07-08
💻 computer science

TrOCR for Medieval HTR: A Systematic Ablation Study with Cross-Dataset Validation

This paper presents a systematic ablation study on adapting TrOCR for medieval handwritten text recognition, demonstrating that specific layer freezing strategies and the removal of contrast normalization can achieve competitive accuracy on small historical datasets while providing cross-dataset validation and interpretability insights.

Sachin Sharma, Federico Simonetta, Michele Flammini2026-07-08
💻 computer science

TOPIC: Deep Learning Approach for Network Intrusion Detection and Multi-Class Attack Classification Using UNSW-NB15 Dataset

This study proposes a deep learning framework using the UNSW-NB15 dataset for network intrusion detection and multi-class attack classification, demonstrating that an RNN-LSTM architecture outperforms ANN and CNN models by achieving a 97.42% accuracy through optimized data preprocessing and class balancing techniques.

Akpasam Ekanem, Philip Asuquo, Simeon Ozoumba, Bliss Stephen, Enyinihi Johnson2026-07-08
💻 computer science

Leveraging Machine Learning Models to Predict Probability of Technical and Regulatory Success

This paper demonstrates that interpretable machine learning models trained on public ClinicalTrials.gov protocol features can accurately predict the probability of technical and regulatory success for small-molecule trials, outperforming standard benchmarks and offering a reproducible tool for risk-adjusted valuation.

Mason Kim, Michael Doane, James Melican, Kevin Wang, Haewon Jung, Cedric Liu2026-07-08
💻 computer science

SupCon-Mamba: A Supervised Contrastive Learning Method for Few-Shot Hyperspectral Target Detection

The paper proposes SupCon-Mamba, a few-shot hyperspectral target detection framework that integrates a local context encoding mechanism, a pyramid Mamba module for efficient multi-scale spectral modeling, and supervised contrastive learning to eliminate false negatives and achieve superior detection performance with minimal labeled samples.

Xingxin Song, Bing Zhou, Jiale Zhao, Lei Deng, Jiaju Ying2026-07-08
💻 computer science

Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference

This paper introduces AIMAPP, a self-supervised, ROS-compatible framework that unifies online mapping, localisation, and planning for autonomous robots in unfamiliar environments by leveraging Active Inference to dynamically build sparse topological maps and balance exploration with goal-directed navigation without relying on predefined maps or pre-training.

Daria de Tinguy, Tim Verbelen, Emilio Gamba, Bart Dhoedt2026-07-08
💻 computer science

Bitcoin Forecasting Engine: Optimizing Neural Networks with Spectral Analysis and Multi Swarm Algorithms

This paper proposes a hybrid Bitcoin forecasting engine that integrates Permutation Entropy-guided dual-layer signal decomposition (CEEMDAN-VMD) with a Multi-Swarm Optimization-optimized Deep Neural Network, demonstrating statistically significant superior performance in accuracy and directional prediction compared to baseline models and single-swarm alternatives.

Ozan Nadirgil2026-07-08