2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration by Ke-Yu Yao, Derek Ka-Hei Lai, Hyo-Jung Lim, Bryan Pak-Hei So, Andy Chi-Ho Chan, Patrick Yiu-Man Yip, Duo Wai-Chi Wong, Bingyang Dai, Xin Zhao, Siu Hong Dexter Wong, James Chung-Wai Cheung

“…Integrated with a fine-tuned InceptionTime deep learning model, it achieves an F1-score of 98 % in classifying Dysphagia Diet Standardization Initiative (IDDSI)-standard swallowing activities, demonstrating its potential for AI-driven health monitoring applications.…”
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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

“…Even though the MODIS and VIIRS BRDF products originate from sensors and algorithms with similar designs, the consistency between BRDF parameters for different sensors is still unknown, and this likely affects the consistency and accuracy of various downstream parameter inversions. …”
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New directions in mapping the Earth’s surface with citizen science and generative AI by Linda See, Qingqing Chen, Andrew Crooks, Juan Carlos Laso Bayas, Dilek Fraisl, Steffen Fritz, Ivelina Georgieva, Gerid Hager, Martin Hofer, Myroslava Lesiv, Žiga Malek, Milutin Milenković, Inian Moorthy, Fernando Orduña-Cabrera, Katya Pérez-Guzmán, Dmitry Schepaschenko, Maria Shchepashchenko, Jan Steinhauser, Ian McCallum

“…Yet the accuracy of these maps is still limited by the lack of in situ data needed to train machine learning algorithms. …”
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Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort by Kyndaron Reinier, Harpriya S. Chugh, Audrey Uy-Evanado, Elizabeth Heckard, Marco Mathias, Nichole Bosson, Vinicius F. Calsavara, Piotr J. Slomka, David A. Elashoff, Alex A.T. Bui, Sumeet S Chugh

“…This paper describes the rationale, objectives, and study design for the OSCAR cohort. …”
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A novel machine learning models for meteorological drought forecasting in the semi-arid climate  region by Chaitanya Baliram Pande, Dinesh Kumar Vishwakarma, Aman Srivastava, Kanak N. Moharir, Fahad Alshehri, Norashidah Md Din, Lariyah Mohd Sidek, Bojan Đurin, Abebe Debele Tolche

“…Abstract The central region of Maharashtra, India, is susceptible to agriculture, meteorological, and hydrological droughts, impacting local ecosystems. The scarcity of historical data  impedes monitoring and forecasting regional droughts. …”
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Development of a Mobile Intervention for Procrastination Augmented With a Semigenerative Chatbot for University Students: Pilot Randomized Controlled Trial by Seonmi Lee, Jaehyun Jeong, Myungsung Kim, Sangil Lee, Sung-Phil Kim, Dooyoung Jung

“…Therefore, we developed and integrated a semigenerative chatbot named Moa into a to-do app. …”
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Descriptions of self-treatment for the middle-aged and elderly in Shanxi, China. by Rui Wang, Chenjin Ma, Kun Jiang, Ming Li, Shuangge Ma

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Computer Viewing Model for Classification of Erythrocytes Infected with <i>Plasmodium</i> spp. Applied to Malaria Diagnosis Using Optical Microscope by Eduardo Rojas, Irene Cartas-Espinel, Priscila Álvarez, Matías Moris, Manuel Salazar, Rodrigo Boguen, Pablo Letelier, Lucia San Martín, Valeria San Martín, Camilo Morales, Neftalí Guzmán

“…Diagnosis is carried out by an optical microscope and depends on operator experience. …”
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Exploring the Global and Regional Factors Influencing the Density of <i>Trachurus japonicus</i> in the South China Sea by Mingshuai Sun, Yaquan Li, Zuozhi Chen, Youwei Xu, Yutao Yang, Yan Zhang, Yalan Peng, Haoda Zhou

“…Height defines the vertical habitat range acoustically detectable, intrinsically linking directly to the vertical distribution and availability of the fish stock itself. …”
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A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…In step 3, after filtering out non-grassland pixels, the performance of RF, SVM, and GTB classifiers was evaluated with combined S1 and S2 data to distinguish different grassland types. Eighty-nine multitemporal raster-based variables, including spectral bands, SAR backscatters, and digital elevation models (DEM), were input for ML models. …”
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LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping by Jonas Schmidinger, Sebastian Vogel, Viacheslav Barkov, Anh-Duy Pham, Robin Gebbers, Hamed Tavakoli, Jose Correa, Tiago R. Tavares, Patrick Filippi, Edward J. Jones, Vojtech Lukas, Eric Boenecke, Joerg Ruehlmann, Ingmar Schroeter, Eckart Kramer, Stefan Paetzold, Masakazu Kodaira, Alexandre M.J.-C. Wadoux, Luca Bragazza, Konrad Metzger, Jingyi Huang, Domingos S.M. Valente, Jose L. Safanelli, Eduardo L. Bottega, Ricardo S.D. Dalmolin, Csilla Farkas, Alexander Steiger, Taciara Z. Horst, Leonardo Ramirez-Lopez, Thomas Scholten, Felix Stumpf, Pablo Rosso, Marcelo M. Costa, Rodrigo S. Zandonadi, Johanna Wetterlind, Martin Atzmueller

“…MLR and SVR performed better on high-dimensional spectral datasets, likely due to better compatibility with principal components. …”
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Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol by Martin Eklund, Brett Delahunt, Lars Egevad, Hemamali Samaratunga, Mattias Rantalainen, Marcello Gambacorta, Einar Gudlaugsson, Bodil Ginnerup Pedersen, Xiaoyi Ji, Karina Dalsgaard Sørensen, Kelvin Szolnoky, Nita Mulliqi, Anders Blilie, Henrik Olsson, Matteo Titus, Geraldine Martinez Gonzalez, Sol Erika Boman, Masi Valkonen, Svein Reidar Kjosavik, José Asenjo, Paolo Libretti, Marcin Braun, Radzislaw Kordek, Roman Łowicki, Kristina Hotakainen, Päivi Väre, Benedicte Parm Ulhøi, Pekka Ruusuvuori, Toyonori Tsuzuki, Emilius Adrianus Maria Janssen, Kimmo Kartasalo

“…However, external validations on diverse data sets have been limited and often show reduced performance. …”
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Human motor control during movements with high demands by Paul Kaufmann, Willi Koller, Elias Wallnöfer, Basilio Goncalves, Clara Scheer, Juliana Exel, Olivia Froschauer, Catherine Hlavac, Mathias Wiplinger, Lorenz Zweier, Arnold Baca, Hans Kainz

“…Nature Neuroscience, 5, 1226-1235. https://doi.org/10.1038/nn963 Turpin, N. A., Uriac, S., & Dalleau, G. (2021). …”
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What happens between first symptoms and first acute exacerbation of COPD – observational study of routine data and patient survey by Alex Bottle, Alex Adamson, Xiubin Zhang, Benedict Hayhoe, Jennifer K Quint

“…Patients had to have at least 1 year’s registration with the GP before the diagnosis date. Patient characteristics were described for the year up to and including the diagnosis date; GP actions were also described in the year before and since diagnosis. …”
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Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures by Luigi Coppolino, Salvatore D'Antonio, Valerio Formicola, Luigi Romano

“…The Dempster-Shafer (DS) theory of evidence has significant weaknesses when dealing with conflicting information sources, as demonstrated by preeminent mathematicians. …”
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Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast. by Jingru Dong, Ruijiao Lei, Feiyang Ma, Lu Yu, Lanlan Wang, Shangzhi Xu, Yunhua Hu, Jialin Sun, Wenwen Zhang, Haixia Wang, Li Zhang

“…More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant organs. …”
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A Neutrosophic Logic Ruled Based Machine Learning Approaches for Chronic Kidney Disease Risk Prediction by Bhabani S. Mohanty, Krishna Priya R, Liya Alias, R. Vijaya Kumar Reddy, Prasanta Kumar Raut, Samson Isaac, Manibharathi.D, C. Saravanakumar, Nihar Ranjan Panda, Said Broumi

“…Chronic kidney disease (CKD) represents a significant global health challenge in society, and early detection of risk is essential for on-time treatment and intervention. …”
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Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

“…Also, the findings emphasize the potential relevance of AI algorithms in addressing complex diagnostic challenges and supporting clinical decisions.This research lays the foundation for developing robust and generalizable models that can advance precision oncology in cancer diagnostics.…”
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Exploring the application of machine learning and SHAP explanations to predict health facility deliveries in Somalia by Jamilu Sani, Salad Halane, Mohamed Mustaf Ahmed, Abdiwali Mohamed Ahmed, Jamal Hassan Mohamoud

“…These findings underscore the potential of ML in designing targeted data-driven interventions to improve maternal health outcomes in Somalia.…”
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A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images by Guannan Chen, Gaoqiang Liu, Xiaoqin Zhu, Mingyu Liu, Encai Zhang, Jichun Li, Kun Zhang, Lihang Lin

“…Tamura texture features could be measured for all input patterns to set up a regression model about the age of scars and that give well-distributed results. Generalized boosted regression trees were calculated with the computed data, and R² and root-mean-square error (RMSE) statistical analysis were used to determine accuracy. …”
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