YOLOv8 framework for COVID-19 and pneumonia detection using synthetic image augmentation by Uddin A Hasib, Raihan Md Abu, Jing Yang, Uzair Aslam Bhatti, Chin Soon Ku, Lip Yee Por

“…Objective Early and accurate detection of COVID-19 and pneumonia through medical imaging is critical for effective patient management. …”
Get full text

Effective Detection of Malicious Uniform Resource Locator (URLs) Using Deep-Learning Techniques by Yirga Yayeh Munaye, Aneas Bekele Workneh, Yenework Belayneh Chekol, Atinkut Molla Mekonen

“…The rapid growth of internet usage in daily life has led to a significant increase in cyber threats, with malicious URLs serving as a common cybercrime. Traditional detection methods often suffer from high false alarm rates and struggle to keep pace with evolving threats due to outdated feature extraction techniques and datasets. …”
Get full text

Incremental Cotton Diseases Detection Based on Aerial Remote Sensing Image and Blockchain Sharding by Jing Nie, Haochen Li, Yang Li, Jingbin Li, Xuewei Chao, Sezai Ercisli

“…Based on the incremental detection model, this article combines the UAV and blockchain sharding technology to create a new cotton pest and disease detection framework, UAV-IFOD-shard. …”
Get full text

Rapid detection and typing of Staphylococcus aureus based on nanopore Cas9-targeted sequencing by PAN Shufan, YANG Donglei, WANG Pengfei

“…Objective·To achieve the rapid detection of Staphylococcus aureus using nanopore Cas9-targeted sequencing (nCATS) technology, and simultaneously perform staphylococcal protein A (spa) typing and staphylococcal cassette chromosome mec (SCCmec) typing.Methods·The spa gene and SCCmec gene elements were selected as two regions of interest (ROIs) for targeted sequencing. …”
Get full text

An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors by Atcharawan Rattanasak, Talit Jumphoo, Wongsathon Pathonsuwan, Kasidit Kokkhunthod, Khwanjit Orkweha, Khomdet Phapatanaburi, Pattama Tongdee, Porntip Nimkuntod, Monthippa Uthansakul, Peerapong Uthansakul

“…The findings substantiate the efficacy of the proposed approach in detecting fetal movements, thereby demonstrating a practical and valuable technology for fetal movement detection applications.…”
Get full text

A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…The conventional artificial diagnosis is time-consuming and relies on the clinical experience of radiologists. To detect gliomas more efficiently, this paper proposes a noninvasive automatic diagnosis system for gliomas based on the machine learning methods. …”
Get full text

Rapid and Highly Sensitive Detection of Ricin in Biological Fluids Using Optical Modulation Biosensing by Eliana Levy, Linoy Golani-Zaidie, Shmuel Burg, Efi Makdasi, Ron Alcalay, Reut Falach, Ofir Schuster, Amos Danielli

“…Rapid, ultra-sensitive detection is crucial for timely medical intervention and implementing security measures. …”
Get full text

Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images by Rashid Abbasi, Farhan Amin, Amerah Alabrah, Gyu Sang Choi, Salabat Khan, Md. Belal Bin Heyat, Muhammad Shahid Iqbal, Huiling Chen

Get full text

Development of Immunoassays for Foodborne Pathogenic Bacteria Detection Using PolyHRP for Signal Enhancement by Yijia Zhang, Junkang Pan, Qiyi He, Zhihao Xu, Bruce D. Hammock, Dongyang Li

“…Compared to the method using SA-HRP, substitution with SA-PolyHRP significantly improved detection sensitivity, achieving limits of detection (LODs) of 1.4 × 10⁴ CFU/mL for <i>E. coli</i> O157:H7 and 6.0 × 10³ CFU/mL for <i>S. …”
Get full text

A stacked ensemble approach to detect cyber attacks based on feature selection techniques by Wahida Ferdose Urmi, Mohammed Nasir Uddin, Md Ashraf Uddin, Md. Alamin Talukder, Md. Rahat Hasan, Souvik Paul, Moumita Chanda, John Ayoade, Ansam Khraisat, Rakib Hossen, Faisal Imran

“…Results show that RFE achieves 100% accuracy for Brute Force attacks, 99.99% for Infiltration and Web Attacks on CICIDS2017, and 99.95% accuracy for all attacks on NSL-KDD, marking a significant improvement over traditional methods. This study demonstrates that optimizing feature selection and leveraging diverse classifiers can substantially enhance the accuracy of CADS, providing stronger protection against evolving cyber threats.…”
Get full text

NeuroFuzzXAI: A Hybrid Artificial Intelligence Framework for Epileptic Seizure Detection by Flavia COSTI, Emanuel COVACI, Ovidiu ROMAN, Darian ONCHIS

“… Background and Aim: Detecting epileptic seizures from electroencephalogram (EEG) recordings is crucial for accurate diagnosis and treatment. …”
Get full text

Transfer learning driven fake news detection and classification using large language models by Basma S. Alqadi, Suliman A. Alsuhibany, Samia Nawaz Yousafzai, Sharf Alzu’bi, Deema Mohammed Alsekait, Diaa Salama AbdElminaam

“…To address these limitations, our approach fills the gap by combining multi-stage transfer learning with embedding comparisons and task-specific optimizations, enabling more robust and accurate detection on small datasets. …”
Get full text

Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…This method incorporates a small target detection layer to optimize the receptive field range, aiming to focus on identifying shallow and small cracks. …”
Get full text

AHG-YOLO: multi-category detection for occluded pear fruits in complex orchard scenes by Na Ma, Na Ma, Na Ma, Yile Sun, Yile Sun, Chenfei Li, Chenfei Li, Zonglin Liu, Zonglin Liu, Haiyan Song, Haiyan Song

“…IntroductionTo achieve fast detection of pear fruits in natural pear orchards and optimize path planning for harvesting robots, this study proposes the AHG-YOLO model for multi-category detection of pear fruit occlusion in complex orchard environments.MethodsUsing the Red Delicious pear as the research object, the pears are classified into three categories based on different occlusion statuses: non-occluded fruits (NO), fruits occluded by leaves/branches (OBL), and fruits in close contact with other fruits but not obstructed by leaves/branches (FCC). …”
Get full text

Dual-Branch Deep Learning with Dynamic Stage Detection for CT Tube Life Prediction by Zhu Chen, Yuedan Liu, Zhibin Qin, Haojie Li, Siyuan Xie, Litian Fan, Qilin Liu, Jin Huang

Get full text

Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…Current surveillance systems and diagnostic methods are limited by infrastructural gaps, insufficient skilled personnel, and inadequate reporting, leading to delays in outbreak detection and response. …”
Get full text

Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…Surface-Enhanced Raman Spectroscopy (SERS) substrates offer a promising solution for the sensitive and specific detection of agrochemicals, enabling timely interventions to mitigate their harmful effects on humans and ecosystems. …”
Get full text

AI-ready rectal cancer MR imaging: a workflow for tumor detection and segmentation by Heather M. Selby, Yewon A. Son, Vipul R. Sheth, Todd H. Wagner, Erqi L. Pollom, Arden M. Morris

“…By combining the radiologist's clinical expertise with the data scientists’ imaging analysis skills, we sought to establish a foundation for future AI-driven approaches that streamline rectal tumor detection and segmentation, and optimize workflow efficiency. …”
Get full text

Detection of Citrus Huanglongbing in Natural Field Conditions Using an Enhanced YOLO11 Framework by Liang Cao, Wei Xiao, Zeng Hu, Xiangli Li, Zhongzhen Wu

“…Existing methods often suffer from insufficient dataset diversity and poor generalization, and struggle to accurately detect subtle early-stage lesions and multiple HLB symptoms in natural backgrounds. …”
Get full text

Ultra-sensitive in situ detection of intracellular Mycobacterium tuberculosis with CRISPR/Cas12a by Zhiqiang Lin, Zhe Song, Hong Yu, Yang Zhou, Yang Zhou, Deliang Liu, Peize Zhang, Li Wei, Guiqin Dai, Guangyan Liang, Zhuojun He, Xiaorong Hu, Yuying Chen, Yuying Chen, Pengfei Zhao, Hongzhou Lu, Mingbin Zheng, Mingbin Zheng

“…Rapid and specific detection of intracellular Mtb is crucial for accurate diagnosis and optimizing treatment strategies. …”
Get full text