Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

“…Therefore, it is required to determine the machine learning model with the best response and F1 score for class 1.Materials and Methods. An open-source data set from the Israelita Albert Einstein Hospital in São Paulo, Brazil, was taken as a basis. …”
Get full text

You Only Look Once v5 and Multi-Template Matching for Small-Crack Defect Detection on Metal Surfaces by Pallavi Dubey, Seth Miller, Elif Elçin Günay, John Jackman, Gül E. Kremer, Paul A. Kremer

“…The lack of large datasets for small metal-surface defects has inhibited the adoption of automation in small-defect detection in remanufacturing settings. This motivated this preliminary study to compare template-based approaches, like MTM, with feature-based approaches, such as DL models, for small-defect detection on an initial laboratory and remanufacturing industry dataset. …”
Get full text

WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…While applying learning techniques to intrusion detection, researchers are facing challenges mainly due to the imbalanced training sets and the high dimensionality of datasets, resulting from the scarcity of attack data and longer training periods, respectively. …”
Get full text

Exploring the feasibility of EEG for pre-hospital detection of medium and large vessel occlusion strokes: a proof-of-concept study by William Peterson, Nithya Ramakrishnan, David Tinklepaugh, Adrian Hamburger, Arthur Kowell, Krag Browder, Nerses Sanossian, Nerses Sanossian, Peggy Nguyen, Ezekiel Fink

“…Current pre-hospital diagnostic methods are limited in sensitivity, delaying treatment for ischemic stroke candidates eligible for endovascular thrombectomy (EVT).MethodsThis proof-of-concept study explores the feasibility of using electroencephalography (EEG) as a diagnostic tool for pre-hospital detection of MeVO and LVO strokes. Conducted in the emergency department setting, this study assessed the efficacy of quantitative EEG biomarkers in differentiating MeVO/LVO-positive cases (n = 4) from MeVO/LVO-negative cases (n = 23). …”
Get full text

Evaluating AI-Based Mitosis Detection for Breast Carcinoma in Digital Pathology: A Clinical Study on Routine Practice Integration by Clara Simmat, Loris Guichard, Stéphane Sockeel, Nicolas Pozin, Rémy Peyret, Magali Lacroix-Triki, Catherine Miquel, Arnaud Gauthier, Marie Sockeel, Sophie Prévot

“…<b>Results:</b> A clinical study evaluating the tool’s performance on routine data clearly demonstrated the value of this approach. …”
Get full text

Early Fault Detection in Electro-Pneumatic Actuators using Mathematical Modelling and Machine Learning: A Bottling Company Case Study by Samuel Olufemi Amudipe, Adeyinka Moses Adeoye, Aderonke Oluwaseunfunmi Akinwumi, Rotimi Adedayo Ibikunle, Segun Adebayo

“…Real-time measurement points were validated through a baseline reference and machine learning models based on support vector machines received training data from labelled sets. The application of feature selection methods helped find essential variables to boost performance metrics in models. …”
Get full text

WPD-ResNeSt: Substation Station Level Network Anomaly Traffic Detection Based on Deep Transfer Learning by Ting Yang, Yucheng Hou, Yachuang Liu, Feng Zhai, Rongze Niu

“…The T1-1 substation communication network is constructed on OPNET for abnormal simulations, and the actual network traffic in a 110kV substation is fused with CIC DDoS2019 and KDD99 data sets for the algorithm performance test, respectively. …”
Get full text

Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks by Manal Abdullah Alohali, Hamed Alqahtani, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K., Jaehyuk Cho

“…Computer-aided diagnosis (CAD) systems have significantly improved early cancer detection, but limitations such as high-dimensional feature sets and overfitting issues persist. …”
Get full text

Carbapenemase Production and Detection of Colistin-Resistant Genes in Clinical Isolates of Escherichia Coli from the Ho Teaching Hospital, Ghana by John Gameli Deku, Kwabena Obeng Duedu, Godsway Edem Kpene, Silas Kinanyok, Patrick Kwame Feglo

“…Effective and successful treatment of infectious diseases is a significant gain in clinical settings. However, resistance to antibiotics, especially the last-resort medicines, including carbapenems and colistin is on the rise. …”
Get full text

Improved potassium reliability in whole blood through hemolysis detection on the novel GEM Premier 7000 blood gas analyzer by Pighi Laura, Salvagno Gian Luca, Marcazzan Filippo, Rizza Mariateresa, Lippi Giuseppe

Get full text

Economic evaluations of screening strategies for the early detection of colorectal cancer in the average-risk population: A systematic literature review. by Joan Mendivil, Marilena Appierto, Susana Aceituno, Mercè Comas, Montserrat Rué

Get full text

Impact of qualitative, semi-quantitative, and quantitative analyses of dynamic contrast-enhanced magnet resonance imaging on prostate cancer detection. by Farid Ziayee, Tim Ullrich, Dirk Blondin, Hannes Irmer, Christian Arsov, Gerald Antoch, Michael Quentin, Lars Schimmöller

“…Aim of this study is to analyze the clinical benefits of these evaluations of DCE regarding clinically significant prostate cancer (csPCa) detection and grading. 209 DCE data sets of 103 consecutive patients with mpMRI (T2, DWI, and DCE) and subsequent MRI-(in-bore)-biopsy were retrospectively analyzed. …”
Get full text

Comparative analysis of BERT-based and generative large language models for detecting suicidal ideation: a performance evaluation study by Adonias Caetano de Oliveira, Renato Freitas Bessa, Ariel Soares Teles

“…However, despite their potential in supporting suicidal ideation detection, these models have not been validated in a patient monitoring clinical setting. …”
Get full text

Detecting muscle fatigue among community-dwelling senior adults with shape features of the probability density function of sEMG by Jiarui Ou, Na Li, Haoru He, Jiayuan He, Le Zhang, Ning Jiang

“…We further proposed a novel fatigue indicator, Temporal-Mean-Kurtosis (TMK) of channel-averaged kurtosis, to detect fatigue with relatively low computational complexity and adequate sensitivity in community settings. …”
Get full text

Deep learning-based optical coherence tomography and retinal images for detection of diabetic retinopathy: a systematic and meta analysis by Zheng Bi, Jinju Li, Qiongyi Liu, Zhaohui Fang, Zhaohui Fang

“…The meta-analysis revealed a pooled sensitivity of 1.88 (95% CI: 1.45-2.44) and a pooled specificity of 1.33 (95% CI: 0.97-1.84) for the detection of DR using deep learning models. All of the outcome of deep learning-based optical coherence tomography ORs ≥0.785, indicating that all included studies with artificial intelligence assistance produced good boosting results.ConclusionDeep learning-based approaches show high accuracy in detecting diabetic retinopathy from OCT and retinal images, supporting their potential as reliable tools in clinical settings. …”
Get full text

Burned Area Detection in the Eastern Canadian Boreal Forest Using a Multi-Layer Perceptron and MODIS-Derived Features by Hadi Mahmoudi Meimand, Jiaxin Chen, Daniel Kneeshaw, Mohammadreza Bakhtyari, Changhui Peng

“…Despite the computational demands of processing large-scale remote sensing data at 250 m resolution, the MLP modeling approach that we used provides an efficient, effective, and scalable solution for long-term burned area detection. …”
Get full text

A Complex Background SAR Ship Target Detection Method Based on Fusion Tensor and Cross-Domain Adversarial Learning by Haopeng Chan, Xiaolan Qiu, Xin Gao, Dongdong Lu

“…In practical applications, it is often necessary to quickly adapt to new loads, new modes, and new data to detect targets effectively. This presents a cross-domain detection problem that requires further study. …”
Get full text

Early detection of human Mpox: A comparative study by using machine learning and deep learning models with ensemble approach by Madhumita Pal, Francesco Branda, Adel Qlayel Alkhedaide, Ashish K Sarangi, Himansu Bhusan Samal, Lizaranee Tripathy, Binapani Barik, Salah M El-Bahy, Alok Patel, Ranjan K Mohapatra, Lawrence Sena Tuglo, Mona Youssef

“…Conclusion The integration of ML and DL models in an ensemble framework significantly enhances Mpox detection. This AI-driven diagnostic approach offers a scalable, accurate, and efficient solution, particularly in resource-limited settings. …”
Get full text

Real-World Colonoscopy Video Integration to Improve Artificial Intelligence Polyp Detection Performance and Reduce Manual Annotation Labor by Yuna Kim, Ji-Soo Keum, Jie-Hyun Kim, Jaeyoung Chun, Sang-Il Oh, Kyung-Nam Kim, Young-Hoon Yoon, Hyojin Park

“…<b>Background/Objectives</b>: Artificial intelligence (AI) integration in colon polyp detection often exhibits high sensitivity but notably low specificity in real-world settings, primarily due to reliance on publicly available datasets alone. …”
Get full text

Coffee Leaf Rust Disease Detection and Implementation of an Edge Device for Pruning Infected Leaves via Deep Learning Algorithms by Raka Thoriq Araaf, Arkar Minn, Tofael Ahamed

“…An edge device was utilized to deploy real-time detection of CLR with the best-trained model. The detection was successfully executed with high confidence in detecting CLR. …”
Get full text