Large language models for accurate disease detection in electronic health records: the examples of crystal arthropathies by Kim Lauper, Denis Mongin, Nils Bürgisser, Samia Mehouachi, Clement P. Buclin, Delphine S. Courvoisier, Etienne Chalot

“…The framework was further validated on 600 paragraphs assessing ‘Calcium Pyrophosphate Deposition Disease (CPPD)’.Results The LLM-based algorithm outperformed the regex method, achieving a 92.7% (88.7%–95.4%) positive predictive value, a 96.6% (94.6%–97.8%) negative predictive value and an accuracy of 95.4% (93.6%–96.7%) for gout. …”
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Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs by Thomas Hügle, Elisabeth Rosoux, Guillaume Fahrni, Deborah Markham, Tobias Manigold, Fabio Becce

“…In the recently established ACR/EULAR CPPD classification criteria, calcification and OA features of the wrist and hand joints are substantial features.ObjectivesTo develop and test a deep-learning algorithm for automatically and reliably detecting CPPD features in hand radiographs, focusing on calcification of the triangular fibrocartilage complex (TFCC) and metacarpophalangeal (MCP)-2 and -3 joints, in separate or combined models.MethodsTwo radiologists independently labeled a dataset of 926 hand radiographs, yielding 319 CPPD positive and 607 CPPD negative cases across the three sites of interest after adjudicating discrepant cases. …”
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Spectral monitoring technology for gas concentrations of multiple target components in oil and gas leakage detection by Zhirong ZHANG, Pengchao CHEN, Yongjun CAI, Wenyou DU, Zhonglin LI, Yuntao PENG, Pengshuai SUN, Bian WU

“…By leveraging spectral analysis for complex systems and employing a design approach focused on background noise removal, traditional tunable diode laser absorption spectroscopy (TDLAS) technology was integrated with partial least squares (PLS) algorithm, non-negative least squares (NNLS) algorithm, and artificial intelligence models. …”
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Exploring Multi-Pathology Brain Segmentation: From Volume-Based to Component-Based Deep Learning Analysis by Ioannis Stathopoulos, Roman Stoklasa, Maria Anthi Kouri, Georgios Velonakis, Efstratios Karavasilis, Efstathios Efstathopoulos, Luigi Serio

“…Detection and segmentation of brain abnormalities using Magnetic Resonance Imaging (MRI) is an important task that, nowadays, the role of AI algorithms as supporting tools is well established both at the research and clinical-production level. …”
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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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Detection Method for Safety Helmet Wearing on Construction Sites Based on UAV Images and YOLOv8 by Xin Jiao, Cheng Li, Xin Zhang, Jian Fan, Zhenwei Cai, Zhenglong Zhou, Ying Wang

“…To address these issues, this study proposes a helmet detection method based on unmanned aerial vehicles (UAVs) and the YOLOv8 object detection algorithm. …”
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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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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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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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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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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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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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“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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Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning by C. Joseph, P. Uma Maheswari

“…Additionally, face emotion detection algorithms tuned with MnasNet-Teaching Learning Based Optimization (TLBO) and Convolution Neural Networks (CNN)-Cuckoo Search Optimization (CSO) are employed for accurate emotion recognition. …”
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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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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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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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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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