Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis. by Rodolfo Rossi, Stanley Zammit, Katherine S Button, Marcus R Munafò, Glyn Lewis, Anthony S David

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Detection of Escherichia coli Using Bacteriophage T7 and Analysis of Excitation‑Emission Matrix Fluorescence Spectroscopy by Nicharee Wisuthiphaet, Huanle Zhang, Xin Liu, Nitin Nitin

“…Conventional detection methods require the isolation and enrichment of bacteria, followed by molecular, biochemical, or culture-based analysis. …”
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Interpretable deep learning for gastric cancer detection: a fusion of AI architectures and explainability analysis by Junjie Ma, Fang Yang, Rong Yang, Yuan Li, Yongjing Chen

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Combining Dielectric and Hyperspectral Data for Apple Core Browning Detection by Hanchi Liu, Jinrong He, Yanxin Shi, Yingzhou Bi

“…To reduce the computational complexity of high-dimensional multi-view data, canonical correlation analysis is employed for feature dimensionality reduction. …”
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Advanced Multi-Scale CNN-BiLSTM for Robust Photovoltaic Fault Detection by Xiaojuan Zhang, Bo Jing, Xiaoxuan Jiao, Ruixu Yao

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Impact of Temporal Resolution on Autocorrelative Features of Cerebral Physiology from Invasive and Non-Invasive Sensors in Acute Traumatic Neural Injury: Insights from the CAHR-TBI... by Nuray Vakitbilir, Rahul Raj, Donald E. G. Griesdale, Mypinder Sekhon, Francis Bernard, Clare Gallagher, Eric P. Thelin, Logan Froese, Kevin Y. Stein, Andreas H. Kramer, Marcel J. H. Aries, Frederick A. Zeiler

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Excitation–Emission Fluorescence Mapping Analysis of Microplastics That Are Typically Pollutants by Syed Atif Iqrar, Aisha Bibi, Raghavan Chinnambedu Murugesan, Daniel Hill, Alex Rozhin

“…To protect these ecosystems, the development of reliable technologies for MNP detection, characterisation, and removal is vital. …”
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ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering by Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif, Nasrin Shabani

“…A robust ML-driven churn analysis depends on a well-developed feature engineering process. …”
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GenVis: Visualizing Genre Detection in Movie Trailers for Enhanced Understanding by Faheem Shaukat, Naveed Ejaz, Zeeshan Ashraf, Mrim M. Alnfiai, Mona Mohammed Alnahari, Reemiah Muneer Alotaibi

“…Automatic movie genre detection is vital for improving content recommendations, user experiences, and organization. …”
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Vibrational spectroscopy unveils distinct cell cycle features of cancer stem cells in melanoma by Bensu Rüya Uslu, Berrin Ozdil, Enver Tarhan, Serdar Özçelik, Hüseyin Aktuğ, Günnur Güler

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TFDGiniXML: A Novel Explainable Machine Learning Framework for Early Detection of Cardiac Abnormalities Based on Nonlinear Time-Frequency Distribution Gini Index Features by Mohamed Aashiq, Shaiful Jahari Hashim, Fakhrul Zaman Rokhani, Marsyita Hanafi, Ahmed Faeq Hussein

“…These features are extracted using the Choi-Williams Time-Frequency method, reporting the first instance application of GI measures to nonlinear time-frequency distribution (TFD) for ECG analysis. …”
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Detection of Broken Rotor Bars in Presence of Load Oscillations by Klemen Drobnic, Mitja Nemec, Henrik Lavric, Vanja Ambrozic, Rastko Fiser

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Investigation of Features of Mass-Fragmentation of Some N-(N,N-diethylacetamidino)-O-alkylfluorophosphates and Related Alkylfluorophosphonates and their Detection by Liquid Chro... by A. V. Braun, I. V. Rybalchenko, V. N. Fateenkov, V. A. Yashkir

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Multi-step attack detection method based on network communication anomaly recognition by Ankang JU, Yuanbo GUO, Tao LI, Ziwei YE

“…In view of the characteristics of internal fixed business logic,inbound and outbound network access behavior,two classes and four kinds of abnormal behaviors were defined firstly,and then a multi-step attack detection method was proposed based on network communication anomaly recognition.For abnormal sub-graphs and abnormal communication edges detection,graph-based anomaly analysis and wavelet analysis method were respectively proposed to identify abnormal behaviors in network communication,and detect multi-step attacks through anomaly correlation analysis.Experiments are carried out on the DARPA 2000 data set and LANL data set to verify the results.The experimental results show that the proposed method can effectively detect and reconstruct multi-step attack scenarios.The proposed method can effectively monitor multi-step attacks including unknown feature types.It provides a feasible idea for detecting complex multi-step attack patterns such as APT.And the network communication graph greatly reduces the data size,it is suitable for large-scale enterprise network environments.…”
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Topological data analysis and machine learning for COVID-19 detection in CT scan lung images by Rabih Assaf, Abbas Rammal, Alban Goupil, Mohammad Kacim, Valeriu Vrabie

“…Our primary objective is to achieve exceptional accuracy in the detection of COVID-19 all while showcasing the effectiveness of these topological features. …”
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Analysis of Basic Compounds in a Network Intrusion Detection System using NSL-KDD Data by Naglaa Ibrahim, Hana Usman

“…In order to get rid of  redundancy and inappropriate features  principle component analysis  (PCA) is useful for selecting features. …”
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Radiomics analysis based on plain X-rays to detect spinal fractures with posterior wall injury by Wangmi Liu, Xiaxuan Zhang, Ruofu Tang, Chengcheng Yu, Guofang Sun

“…Radiomic features were extracted from both anteroposterior and lateral plain spine radiographs to evaluate the utility of radiomics in detecting posterior wall injury. …”
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Detection of Wood Boring Insects’ Larvae Based on the Acoustic Signal Analysis and the Artificial Intelligence Algorithm by Piotr BILSKI, Piotr BOBIŃSKI, Adam KRAJEWSKI, Piotr WITOMSKI

“…The results allowed us to assess the effectiveness of the old house borer’s detection by the acoustic analysis enhanced with the AI algorithm.…”
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PRIVACY-AWARE MALARIA DETECTION: U-NET MODEL WITH K-ANONYMITY FOR CONFIDENTIAL IMAGE ANALYSIS by Ghazala Hcini, Imen Jdey

“…Malaria detection through cell image analysis is essential for early diagnosis and effective treatment, as timely detection can significantly reduce the risk of severe health complications. …”
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Detection of tuberculosis using cough audio analysis: a deep learning approach with capsule networks by Sakthi Jaya Sundar Rajasekar, Anu Rithiga Balaraman, Deepa Varnika Balaraman, Saleem Mohamed Ali, Kannan Narasimhan, Narayanasamy Krishnasamy, Varalakshmi Perumal

“…Abstract Purpose Tuberculosis (TB) is a widespread infectious disease that requires early detection for effective treatment and control. This study aims to improve TB detection using cough audio analysis, comparing the performance of capsule networks to other deep learning models. …”
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