AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study by Tai-Han Lin, Hsing-Yi Chung, Ming-Jr Jian, Chih-Kai Chang, Hung-Hsin Lin, Chiung-Tzu Yen, Sheng-Hui Tang, Pin-Ching Pan, Cherng-Lih Perng, Feng-Yee Chang, Chien-Wen Chen, Hung-Sheng Shang

“…The primary objective was to implement this model within an artificial intelligence–clinical decision support system (AI-CDSS) to enhance early sepsis detection and management in critical care settings. …”
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Object Detection in Ground-Penetrating Radar Images Using a Deep Convolutional Neural Network and Image Set Preparation by Migration by Kazuya Ishitsuka, Shinichiro Iso, Kyosuke Onishi, Toshifumi Matsuoka

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Evaluation of a two-question screening tool in the detection of intimate partner violence in a primary healthcare setting in South Africa by A. Saimen, E. Armstrong, C. Manitshana, I. Govender

“…Currently the concept of using a screening tool to detect intimate partner violence has not been widely explored in a primary healthcare setting in South Africa, and for this reason the current study was undertaken. …”
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Molecular detection of and in patients with soft tissue infections in a tertiary hospital setting, Calabar, Nigeria: a cross-sectional study by Christian J. Ide, Godwin I. Ogban, Bassey E. Ekeng, Ubleni E. Emanghe, Asukwo E. Onukak, Anthony A. Iwuafor, Ubong A. Udoh, Stella T. Chukwuma, Emmanuel M. Jimmy, Ido E. Ukpeh, Tatfeng Y. Mirabeau, Daniel Z. Egah

“…Several studies have shown that methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) are carriers of the lukSF-PV ; however, data describing their prevalence and distribution in the Nigerian setting are sparse in the literature, and thus informed the need for the current study. …”
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Bringing lab to the field: Exploring innovations in point-of-care diagnostics for the rapid detection and management of tropical diseases in resource-limited settings by Abdullahi Tunde Aborode, Ridwan Olamilekan Adesola, Godfred Yawson Scott, Emele Arthur-Hayford, Oche Joseph Otorkpa, Somuah Daniel Kwaku, Emmanuel Ebuka Elebesunu, Eghaghe Osadebamwen Nibokun, Ibude Jane Aruorivwooghene, Adetolase A. Bakre, Oluwaseun Adeolu Ogundijo, Olamilekan Gabriel Banwo, Oluwatobiloba Ige, Ibrahim O. Adelakun, Isreal Ayobami Onifade, Segun E. Ogungbemi, Boluwatife T. Dosunmu, Oluwaseunayo Deborah Ayando, Nike Idowu, Grace A. Adegoye, Olusegun Oluwaseun Jimoh

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Detection of risk for depression among adolescents in diverse global settings: protocol for the IDEA qualitative study in Brazil, Nepal, Nigeria and the UK by Christian Kieling, Brandon A Kohrt, Syed Shabab Wahid, Gloria A. Pedersen, Katherine Ottman, Abigail Burgess, Kamal Gautam, Thais Martini, Anna Viduani, Olufisayo Momodu, Crystal Lam, Helen L. Fisher, Abiodun O Adewuya, Valeria Mondelli

“…This is a multisite qualitative study being conducted in Brazil, Nepal, Nigeria and the UK.Methods and analysis A systematic set of qualitative methods will be used in this study. …”
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study by Inge A. H. van den Berk, Colin Jacobs, Maadrika M. N. P. Kanglie, Onno M. Mets, Miranda Snoeren, Alexander D. Montauban van Swijndregt, Elisabeth M. Taal, Tjitske S. R. van Engelen, Jan M. Prins, Shandra Bipat, Patrick M. M. Bossuyt, Jaap Stoker, The OPTIMACT study group

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Detection Framework for Few-Shot Voltage Disturbances in Power Systems Using Evaluation Learning by Wenxia Sima, Han Zhang, Ming Yang

“…Data-driven detection models for voltage disturbance in power systems have performed exceptionally over the years. …”
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Study and Developing a Network Security Prototype Based on Agent Technology by Najla Ibraheem, Haleema Sulaiman

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DynaOOD-Net: Dynamic Progressive Feature Fusion and Energy Balancing for Robust Out-of-Distribution Detection by Jiting Zhou, Zhihao Zhou, Pu Zhang

“…In the field of object detection in open environments, models are required to simultaneously recognize predefined categories and accurately distinguish unknown categories from non-object regions, all while addressing the challenges of imbalanced data distributions and multi-scale targets. …”
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MTAHG and MTBHG: Modified Approaches for Interpreting Gravity Data by Hazel Deniz Toktay, Hanbing Ai, Ahmad Alvandi, Kejia Su, Jinlei Li

“…Two high‐resolution gravity data sets from the Western Carpathians in Slovakia and the Witwatersrand Basin in South Africa were used to test the applicability of the modified methods. …”
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Development of software interface for AI-driven weed control in robotic vehicles, with time-based evaluation in indoor and field settings by G C Sunil, Arjun Upadhyay, Xin Sun

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Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data. by Tian Xia, Lanju Zhou, Khalil Ahmad

“…This research included the development of abnormal categorisation models, assessment of data recognition quality, and detection of anomalies. …”
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Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data. by Pengyi Yang, Xiaofeng Zheng, Vivek Jayaswal, Guang Hu, Jean Yee Hwa Yang, Raja Jothi

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Private detection of relatives in forensic genomics using homomorphic encryption by Fillipe D. M. de Souza, Hubert de Lassus, Ro Cammarota

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GeneCOCOA: Detecting context-specific functions of individual genes using co-expression data. by Simonida Zehr, Sebastian Wolf, Thomas Oellerich, Matthias S Leisegang, Ralf P Brandes, Marcel H Schulz, Timothy Warwick

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Enhancing counterfactual detection in multilingual contexts using a few shot clue phrase approach by Lekshmi Kalinathan, Karthik Raja Anandan, Jagadish Ravichandran, K. Devi, S. Benila, Abithkumar Ravikumar

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Stretched Gelatin Phantom for Detection of Residual Dipolar Couplings in MR Spectra and Data Analysis of Carnosine by Karel Bernášek, Marián Grocký, Martin Burian, Jan Lang

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Enhancing Brain Tumor Detection: A Comparative Study of CNN Architectures Using MRI Data by Zhu Zhimeng

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ALDExA: Automated LLM-Assisted Detection of CVE Exploitation Attempts in Host-Captured Data by Niclas Ilg, Maximilian Pfitzenmaier, Dominik Germek, Paul Duplys, Michael Menth

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