Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Sentiment analysis (SA) identifies people’s emotions, attitudes, and sentiments towards a given target, like activities, people, services, organizations, products, and subjects. Emotion detection is a subdivision of SA as it forecasts the novel emotion instead of only maintaining negative, positive, or neutral. …”
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The implementation and appraisal of a novel confirmatory HIV-1 testing algorithm in the Microbicides Development Programme 301 Trial (MDP301). by Ute Jentsch, Precious Lunga, Charles Lacey, Jonathan Weber, Janet Cairns, Gisela Pinheiro, Sarah Joseph, Wendy Stevens, Sheena McCormack

“…The overall sample set was >95% complete. 419 (78%) of the rapid test positive samples were confirmed as primary endpoints using a combination of assays for the detection of HIV-specific antibodies (EIA's and Western Blot), and for components of the virus itself (PCR for the detection of nucleic acids and EIA for p24 antigen). 63 (12%) cases were confirmed as being HIV-positive at screening or enrolment and 55 (10%) were confirmed as HIV negative. …”
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The impact of social media messages on Parkinson’s disease treatment: detecting genuine sentiment in patient notes by Hanane Grissette, El Habib Nfaoui

“…It is been crucial to analyze online narratives and detect sentiment in patients’ self-reports. In this paper, we propose an automatic concept-level neural network method to distilling genuine sentiment in patients’ notes as medical polar facts into true positives and true negatives. …”
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Introducing HeliEns: A Novel Hybrid Ensemble Learning Algorithm for Early Diagnosis of <i>Helicobacter pylori</i> Infection by Sultan Noman Qasem

“…HeliEns significantly improved diagnostic accuracy and reliability for early H. infection detection. The integration of multiple quantum ML algorithms within the HeliEns framework enhanced overall model performance. …”
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Real-Time Object Detection for the Running Train Based on the Improved YOLO V4 Neural Network by Yang Liu, Mengfei Gao, Humin Zong, Xinping Wang, Jinshuang Li

“…Lightweight convolutional neural network MobileNet and clustering ideas are combined to improve the object detection algorithm, and the MYOLO-lite model object detection algorithm is designed. …”
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Detection of mare parturition through balanced multi-scale feature fusion based on improved Libra RCNN. by Buyu Wang, Weijun Duan, Jian Zhao, Dongyi Bai

“…Moreover, this study employed a statistical method combined with a sliding window mechanism to assess the algorithm's performance in detecting mare parturition in video stream continuous monitoring scenarios, achieving an accuracy rate of 92.75% for mare parturition detection. …”
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Sparse Decomposition-Based Anti-Spoofing Framework for GNSS Receiver: Spoofing Detection, Classification, and Position Recovery by Yuxin He, Xuebin Zhuang, Bing Xu

“…A sparse decomposition algorithm with non-negative constraints limited by signal power magnitudes is proposed to achieve accurate spoofing detections while extracting key features of the received signals. …”
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“VisualFields Easy”: an iPad Application as a Simple Tool for Detecting Visual Field Defects by Angelane S. Santos, MD, Evelyn S. Morabe, MD

“…Purpose/Objective: This study aims to determine the reliability of the “VisualFields Easy” application in detecting visual field loss among ophthalmology patients; and to determine the sensitivity, specificity, positive predictive and negative predictive values of this examination using the Humphrey Visual Field Analyzer as the gold standard. …”
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Improving Detection of Underlying Neurologic Etiology for Pediatric Cavovarus Foot Deformity: We Can Do Better by Michael O'Sullivan MD, Michelle Christie MD, Rusty Hartman BS, Anthony I. Riccio MD

“…The advanced diagnostic algorithm (ADA) Included all components of the TDA in addition to genetic testing, and/or muscle/nerve biopsy and/or repeat EMG/NCV testing when initial workup remained negative. …”
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Validation study of health administrative data algorithms to identify individuals experiencing homelessness and estimate population prevalence of homelessness in Ontario, Canada by Lucie Richard, Stephen W Hwang, Cheryl Forchuk, Rosane Nisenbaum, Kristin Clemens, Kathryn Wiens, Richard Booth, Mahmoud Azimaee, Salimah Z Shariff

“…Two reference standard definitions of homelessness were adopted: the housing episode and the annual housing experience (any homelessness within a calendar year).Main outcome measures Sensitivity, specificity, positive and negative predictive values and positive likelihood ratios of 30 case ascertainment algorithms for detecting homelessness using up to eight health service databases.Results Sensitivity estimates ranged from 10.8% to 28.9% (housing episode definition) and 18.5% to 35.6% (annual housing experience definition). …”
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Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning by Sandhya Mekala, Phani Kumar S

“…Finally, pancreatic tumor detection is performed by SeWBO_Efficient DenseNet. …”
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A Lightweight TA-YOLOv8 Method for the Spot Weld Surface Anomaly Detection of Body in White by Weijie Liu, Miao Jia, Shuo Zhang, Siyu Zhu, Jin Qi, Jie Hu

“…We developed a TA-YOLOv8 network structure which has an improved Task-Aligned (TA) head detection, designed to handle a small sample size, imbalanced positive and negative samples, and high-noise characteristics of Body-in-White welding spot data. …”
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AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

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Detecting of a Patient&#x0027;s Condition From Clinical Narratives Using Natural Language Representation by Thanh-Dung Le, Rita Noumeir, Jerome Rambaud, Guillaume Sans, Philippe Jouvet

“…<italic>Conclusions:</italic> This study successfully applied learning representation and machine learning algorithms to detect heart failure in a single French institution from clinical natural language. …”
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Extracellular mRNA detected by molecular beacons in tethered lipoplex nanoparticles for diagnosis of human hepatocellular carcinoma. by Xinmei Wang, Kwang Joo Kwak, Zhaogang Yang, Aili Zhang, Xiaoli Zhang, Rachael Sullivan, Dan Lin, Robert L Lee, Carlos Castro, Kalpana Ghoshal, Carl Schmidt, L James Lee

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P-68 LIVGUARD, A DEEP NEURAL NETWORK FOR CIRRHOSIS DETECTION IN LIVER ULTRASOUND (USD) IMAGES by DIEGO ARUFE, Pablo Gomez del Campo, Ezequiel Demirdjian, Carlos Galmarini

“…The AI system achieved an overall detection rate of 88.8%. Sensitivity, specificity, positive (P) and negative (N) predictive values (PV) were 100%, 82.7%, 76.1% and 100%, respectively. …”
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Synergistic detection of E. coli using ultrathin film of functionalized graphene with impedance spectroscopy and machine learning by Amrit Kumar, Shweta Mishra, R. K. Gupta, V. Manjuladevi

“…Machine learning (ML) algorithms applied to raw impedance data improved detection precision and reliability, enabling automated and accurate analysis. …”
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Deep Learning and Automatic Detection of Pleomorphic Esophageal Lesions—A Necessary Step for Minimally Invasive Panendoscopy by Miguel Martins, Miguel Mascarenhas, Maria João Almeida, João Afonso, Tiago Ribeiro, Pedro Cardoso, Francisco Mendes, Joana Mota, Patrícia Andrade, Hélder Cardoso, Miguel Mascarenhas-Saraiva, João Ferreira, Guilherme Macedo

“…Deep-learning (DL) algorithms were developed for the detection of enteric and gastric lesions. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

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Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke by Gianluca Brugnara, Michael Baumgartner, Edwin David Scholze, Katerina Deike-Hofmann, Klaus Kades, Jonas Scherer, Stefan Denner, Hagen Meredig, Aditya Rastogi, Mustafa Ahmed Mahmutoglu, Christian Ulfert, Ulf Neuberger, Silvia Schönenberger, Kai Schlamp, Zeynep Bendella, Thomas Pinetz, Carsten Schmeel, Wolfgang Wick, Peter A. Ringleb, Ralf Floca, Markus Möhlenbruch, Alexander Radbruch, Martin Bendszus, Klaus Maier-Hein, Philipp Vollmuth

“…Here, we developed an artificial neural network (ANN) which allows automated detection of abnormal vessel findings without any a-priori restrictions and in <2 minutes. …”
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