Prognostic predictions in psychosis: exploring the complementary role of machine learning models by Metten Somers, Hugo G Schnack, Rene S Kahn, Diane F van Rappard, Frank L Gerritse, Edwin van Dellen, Violet van Dee, Seyed M Kia, Caterina Fregosi, Wilma E Swildens, Anne Alkema, Albert Batalla, Coen van den Berg, Danko Coric, Lotte G Dijkstra, Arthur van den Doel, Livia S Dominicus, John Enterman, Marte Z van der Horst, Fedor van Houwelingen, Charlotte S Koch, Lisanne E M Koomen, Marjan Kromkamp, Michelle Lancee, Brian E Mouthaan, Eline J Regeer, Raymond W J Salet, Jorgen Straalman, Marjolein H T de Vette, Judith Voogt, Inge Winter-van Rossum, Wiepke Cahn

“…Background Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine learning (ML) shows promise in outcome prediction, it has not yet been integrated into clinical practice. …”
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Morphology reconstruction from experimental small-angle x-ray scattering patterns by physics-aware neural network by Chenhao Zhao, Shenyang Sun, Xueqing Han, Jianhe Zhu, Wancheng Yu, Liangbin Li

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Spatiotemporal Mapping of Grazing Livestock Behaviours Using Machine Learning Algorithms by Guo Ye, Rui Yu

“…This study investigated the spatiotemporal patterns of livestock behaviours under different grazing management systems and grazing-intensity gradients (GIGs) in Wenchang, China, using high-resolution GPS tracking data and machine learning classification. the K-Nearest Neighbours (KNN) model combined with SMOTE-ENN resampling achieved the highest accuracy, with F1-scores of 0.960 and 0.956 for continuous and rotational grazing datasets. …”
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AI Narrative Modeling: How Machines’ Intelligence Reproduces Archetypal Storytelling by Igor Kabashkin, Olga Zervina, Boriss Misnevs

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Four Machine Learning Algorithms for Biometrics Fusion: A Comparative Study by I. G. Damousis, S. Argyropoulos

“…Supervised learning was carried out using a number of patterns from a well-known benchmark biometrics database, and the validation/testing took place with patterns from the same database which were not included in the training dataset. …”
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Reliability process methodology of the centrifugal rotary machining in the medium of steel balls by Denis Vladimirovich Kazakov

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Machine Learning-Based Network Anomaly Detection: Design, Implementation, and Evaluation by Pilar Schummer, Alberto del Rio, Javier Serrano, David Jimenez, Guillermo Sánchez, Álvaro Llorente

“…<b>Methods:</b> This study develops and evaluates a machine learning-based system for network anomaly detection, focusing on point anomalies within network traffic. …”
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Can machine learning distinguish between elite and non-elite rowers? by Orten Kristine Fjellkårstad, Helgesen Sander Elias Magnussen, Chen Bihui, Baselizadeh Adel, Torresen Jim, Herrebrøden Henrik

“…A major challenge for sports coaches and analysts is to identify critical elements of athletes’ movement patterns. A potentially relevant tool is machine learning, useful because of its ability to extract patterns from data. …”
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Automating the amino acid identification in elliptical dichroism spectrometer with Machine Learning. by Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

“…Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. …”
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Machine Learning Techniques to Model and Predict Airflow Requirements in Underground Mining by Maria Karagianni, Andreas Benardos

“…More particularly, ML techniques are utilized to capture patterns or prevailing conditions and to be able to generalize/predict future conditions managed via the ventilation system. …”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…As prolonged inactivity becomes a growing public health concern, researchers are increasingly utilizing machine learning (ML) techniques to examine and understand these patterns. …”
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Assessment of Machine Learning Models for Predicting Aboveground Biomass in the Indian Subcontinent by S. Mamgain, B. Ghale, H. C. Karnatak, A. Roy

“…This study highlights the importance of using robust machine learning models like RF to accurately capture spatial patterns of biomass distribution, which is crucial for forest management, carbon accounting, &amp; biodiversity conservation in the Indian subcontinent.…”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets.  …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets.  …”
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Stock Price Prediction in the Financial Market Using Machine Learning Models by Diogo M. Teixeira, Ramiro S. Barbosa

“…The complexity of advanced models such as XGBoost and GRU is reflected in their overall performance, suggesting that they can be particularly effective at capturing patterns and making accurate predictions in more complex time series, such as stock prices.…”
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Predicting Students’ Performance Using a Hybrid Machine Learning Approach by Ropafadzo Duwati, Tawanda Mudawarima

“…The Linear Support Vector Classifier (SVC) captured linear patterns within the data, and Logistic Regression was employed as a meta-learner to make the final predictions. …”
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An Assessment of Land Use Land Cover Using Machine Learning Technique by V. Pushpalatha, H. N. Mahendra, A. M. Prasad, N. Sharmila, D. Mahesh Kumar, N. M. Basavaraju, G. S. Pavithra and S. Mallikarjunaswamy

“…The study aims to analyze the spatiotemporal patterns of urban expansion, land-use dynamics, and associated factors influencing the city’s built environment. …”
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Anomaly Detection in Data Streams Using Machine Learning and Deep Learning by Muhammad Amin Daneshwar

“…The goal of this anomaly identification in the data streams is to find patterns that deviate substantially from the way things usually work. …”
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Analysis of Partial Discharge Measurements using Coupling Capacitor in Rotating Machine by Ahmad Syukri Abd Rahman, Mohamad Nur Khairul Hafizi Rohani, Nur Dini Athirah Gazata, Afifah Shuhada Rosmi, Ayob Nazmi Nanyan, Aiman Ismail Mohamed Jamil, Mohd Helmy Halim Abdul Majid, Normiza Masturina Samsuddin

“…Additionally, this paper provides a detailed study of PD signal characteristics, specifically focusing on phase-resolved partial discharge (PRPD) patterns, to understand the behavior of PD in HV rotating machines, enhancing fault diagnosis and preventive maintenance strategies.…”
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Machine learning-assisted development of polypyrrole-grafted yarns for e-textiles by Matteo Iannacchero, Joakim Löfgren, Mithila Mohan, Patrick Rinke, Jaana Vapaavuori

“…The optimized yarns are woven into prototype fabrics with different patterns, and we demonstrate their applicability as flexible conductive wearable and heaters.…”
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