A photovoltaic anomaly data identification method based on image feature detection by QIU Yutao, ZHANG Lei, ZHOU Kaiyun, YAN Min, SUN Jintong, LONG Huan

“…To address this， this paper introduces an anomaly data identification algorithm based on image feature detection and dual-threshold processing. …”
Get full text

Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease by Xiachuan Qin, Xiaoling Liu, Linlin Xia, Qi Luo, Chaoxue Zhang

Get full text

Catalyzing early ovarian cancer detection: Platelet RNA-based precision screening by Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Hyejin Lee, Yeochan Kim, Sangick Park, Suyeon Lee, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, Cheol Lee, TaeJin Ahn, Yong-Sang Song

“…Recent advancements in RNA technology from platelets aid in early tumor detection. Here, we proposed our two-step method for assessing the existence of pelvic mass either located at ovaries or uterus with more than 99% specificity by utilizing exon-exon junction features with a sampling invariant normalization technique; then next our model finds the malignancy of detected mass with more than 99% negative predictive value for ovarian cancer to practically assist clinicians’ further investigation via combined features of exon-exon junctions, and hematology parameters. …”
Get full text

Automated Detection of Reduced Ejection Fraction Using an ECG-Enabled Digital Stethoscope by Ling Guo, PhD, Gregg S. Pressman, MD, Spencer N. Kieu, BS, Scott B. Marrus, MD, PhD, George Mathew, PhD, John Prince, PhD, Emileigh Lastowski, MS, Rosalie V. McDonough, MD, MSc, Caroline Currie, BA, John N. Maidens, PhD, Hussein Al-Sudani, MD, Evan Friend, BA, Deepak Padmanabhan, MD, Preetham Kumar, MD, Edward Kersh, MD, Subramaniam Venkatraman, PhD, Salima Qamruddin, MD

“…Recently, electrocardiogram-based algorithms have shown promise in detecting ALVSD. Objectives: The authors developed and validated a convolutional neural network (CNN) model using single-lead electrocardiogram and phonocardiogram inputs captured by a digital stethoscope to assess its utility in detecting individuals with actionably low ejection fractions (EF) in a large cohort of patients. …”
Get full text

Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea) by Degninou Yehadji, Degninou Yehadji, Geraldine Gray, Carlos Arias Vicente, Petros Isaakidis, Petros Isaakidis, Abdourahimi Diallo, Saa Andre Kamano, Thierno Saidou Diallo

Get full text

Detection of left atrial enlargement in dogs using deep learning in thoracic radiographs by Lucas Auto Lopes, Anaemilia das Neves Diniz, Helio Silva Neto

Get full text

Detection of left atrial enlargement in dogs using deep learning in thoracic radiographs by Lucas Auto Lopes, Anaemilia das Neves Diniz, Helio Silva Neto

Get full text

Characterization of Phytoplankton Composition in Lake Maggiore: Integrated Chemotaxonomy for Enhanced Cyanobacteria Detection by Elisabetta Canuti, Martina Austoni

“…Cyanobacterial blooms in lakes have increased in frequency and intensity over the past two decades, negatively affecting ecological and biogeochemical processes. …”
Get full text

Preliminary analysis of acoustic detection of the Red-throated Caracara in northern Costa Rica by Roberto Vargas-Masís, Diego Quesada

“…Advances in automatic acoustic detection have transformed bird ecology, allowing researchers to analyze bird populations using pattern matching algorithms, machine learning, and random forest models. …”
Get full text

Real Time Intrusion Detection System Based on Web Log File Analysis by Rawand Raouf Abdalla, Alaa Khalil Jumaa, Ahmad Freidoon Fadhil

“…In this work, various data preprocessing techniques are applied, and key features are extracted, enhancing the system's ability to effectively detect intrusions. The model was constructed using four machine learning algorithms: gradient-boosted trees, decision tree, random forest, and support vector machine. …”
Get full text

Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…This research focuses on detecting Bot-IoT activity using the Bot-IoT UNSW Canberra 2018 dataset. …”
Get full text

Leveraging SARs and Advanced Deep Learning Techniques for Oil Spill Detection in UAE by M. Alkhalifa, A. Alowais, A. Manousakis, A. Manousakis

“…Accidental oil spills are known to reflect negative outcomes on the environment and human health as well as marine life and coastal regions’ economy. …”
Get full text

Integrating Color and Contour Analysis with Deep Learning for Robust Fire and Smoke Detection by Abror Shavkatovich Buriboev, Akmal Abduvaitov, Heung Seok Jeon

“…This study suggests a unique concatenated convolutional neural network (CNN) model that combines deep learning with hybrid preprocessing methods, such as contour-based algorithms and color characteristics analysis, to provide reliable and accurate fire and smoke detection. …”
Get full text

The inconvenient truth of ground truth errors in automotive datasets and DNN-based detection by Pak Hung Chan, Boda Li, Gabriele Baris, Qasim Sadiq, Valentina Donzella

Get full text

Detecting Freezing of Gait in Parkinson Disease Using Multiple Wearable Sensors Sets During Various Walking Tasks Relative to Medication Conditions (DetectFoG): Protocol for a Pros... by Sébastien Cordillet, Sophie Drapier, Frédérique Leh, Audeline Dumont, Florian Bidet, Isabelle Bonan, Karim Jamal

“…The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the most effective combination of wearable sensors for detecting FoG episodes will be studied. …”
Get full text

Distinguishing Human From Machine: A Review of Advances and Challenges in AI-Generated Text Detection by Serena Fariello, Giuseppe Fenza, Flavia Forte, Mariacristina Gallo, Martina Marotta

“…Results demonstrate that, despite the good delimited performance, the multitude of languages to recognize, hybrid texts, the continuous improvement of algorithms for text generation and the lack of regulation require additional efforts for efficient detection.…”
Get full text

Comparison of K-Nearest Neighbors and Naive Bayes Classifier Algorithms in Sentiment Analysis of 2024 Election in Twitter (X) by Lola Enjelia, Yana Cahyana, Rahmat, Deden Wahiddin

“…This study compares the performance of the K-Nearest Neighbors (K-NN) and Naive Bayes Classifier (NBC) algorithms in sentiment analysis of the 2024 Regional Election (Pilkada) based on Indonesian local data sourced from platform X. …”
Get full text

SARS-CoV-2 Prediction Strategy Based on Classification Algorithms from a Full Blood Examination by C. F. Choukhan, I. Lasri, R. El Hatimi, M. R. Lemnaouar, M. Esghir

Get full text

Smart real-time detection of risky roads using vehicles trajectories for intelligent transportation by Eman O. Eldawy, Mohammed Abdalla, Hoda M.O. Mokhtar, Abdeltawab Hendawi, Amr M. AbdelAziz

Get full text

Evaluation on nature-connected environment in building embedded landscape: theory, detection, and case design by Shu Zhong, Jiao Ren

Get full text