SMART DELAY PREDICTION: SUPERVISED MACHINE LEARNING SOLUTIONS FOR CONSTRUCTION PROJECTS by Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi, Meenakshi Kandpal

“…The findings show that ensemble-based delay prediction models have the potential to reduce the uncertainties related to projects, control delays, schedule resources efficiently, and ultimately improve the infrastructure project efficiency in costing and timely project completion.…”
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Sustainability-driven fertilizer recommender system for coffee crops using case-based reasoning approach by Edinson David León Chilito, Juan Fernando Casanova Olaya, Juan Fernando Casanova Olaya, Juan Carlos Corrales, Cristhian Figueroa

“…Future work will expand the case base and refine recommender algorithms to improve accuracy and usability.…”
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Enhancing Breast Cancer Diagnosis With Multi-Resolution Vision Transformers and Robust Decision-Making by Margo Sabry, Hossam Magdy Balaha, Khadiga M. Ali, Tayseer Hassan A. Soliman, Dibson Gondim, Mohammed Ghazal, Norah Saleh Alghamdi, Ayman El-Baz

“…This study aims to improve breast cancer (BC) diagnosis through a novel multi-resolution Vision Transformer (ViT)-based framework with ensemble decision-making, addressing limitations in traditional single-magnification models. …”
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Impact of imbalanced features on large datasets by Waleed Albattah, Rehan Ullah Khan

“…Distributed Gaussian (D-GA) and Distributed Poisson (D-PO) are found to be the most effective techniques, especially in improving Random Forest (RF) and SVM models. The deep learning experiments also show an improvement as such.…”
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Potassium Fulvate Alleviates Salinity and Boosts Oat Productivity by Modifying Soil Properties and Rhizosphere Microbial Communities in the Saline–Alkali Soils of the Qaidam Basin... by Jie Wang, Xin Jin, Xinyue Liu, Yunjie Fu, Kui Bao, Zhixiu Quan, Chengti Xu, Wei Wang, Guangxin Lu, Haijuan Zhang

“…Structural equation modeling further showed that PF mitigates salinity chiefly by improving soil physicochemical properties (path coefficient = −0.77; <i>p</i> < 0.001), with microbial assemblages acting as key intermediaries. …”
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Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…Our results establish that physics-informed constraints significantly improve both the validity (94.7%) and diversity (0.82 Tanimoto distance) of generated molecular structures compared with unconstrained baselines. …”
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Range Space and Similarity Transformation Using Symbolic Mathematics in Python by Chainarong Wisassakwichai, Prasert Phaochoo

“…The effectiveness of these classes has been validated through numerical results, which, when compared to MATLAB functions (null(), pinv(), sym(), and jordan()), demonstrate that the exact symbolic solutions from both classes significantly improve numerical precision for selected application examples from numerical algorithms, power systems and linear algebra. …”
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Diagnostic value of leukocytosis in patients presenting to the emergency department with abdominal pain: A retrospective observational study by Erkan Boğa

“…Further multicenter prospective studies are needed to validate these findings and improve diagnostic algorithms.…”
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Body-part-based individual feral cat identification from camera trap images using deep learning by Rio Rifqi Syah Akbar, Matthew W. Rees, Patricia A. Fleming, Ferdous Sohel

“…Feral cats (Felis catus) are a significant threat to Australia's native wildlife, contributing to the decline and extinction of at least 20 native mammal species through predation impacts. To improve the identification and monitoring of populations, individual identification of cats is required. …”
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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

“…Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images show promise in improving the accuracy and efficiency of histopathological assessments. …”
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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Results: The regression tree model outperformed all 9 metalearner models. Tree results suggested group-based PT yielded the largest improvement in mean WOMAC score. …”
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Can Different Cultivars of <i>Panicum maximum</i> Be Identified Using a VIS/NIR Sensor and Machine Learning? by Gelson dos Santos Difante, Gabriela Oliveira de Aquino Monteiro, Juliana Caroline Santos Santana, Néstor Eduardo Villamizar Frontado, Jéssica Gomes Rodrigues, Aryadne Rhoana Dias Chaves, Dthenifer Cordeiro Santana, Izabela Cristina de Oliveira, Luis Carlos Vinhas Ítavo, Fabio Henrique Rojo Baio, Gabriela Souza Oliveira, Carlos Antonio da Silva Junior, Vanessa Zirondi Longhini, Alexandre Menezes Dias, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro

“…The objectives of this study were to identify ML models able to differentiate <i>P. maximum</i> cultivars and determine which is the best spectral input for these algorithms and whether reducing the sample size improves the response of the algorithms. …”
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An ensemble machine learning framework with explainable artificial intelligence for predicting haemoglobin anaemia considering haematological markers by Dhruva Darshan B S, Punit Sharma, Krishnaraj Chadaga, Niranjana Sampathila, G. Muralidhar Bairy, Sushma Belurkar, Srikanth Prabhu, Swathi K S

“…The ML models' judgments are interpreted using explainable artificial intelligence (XAI) methods. …”
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Quantitative Analysis of Sulfur Elements in Mars-like Rocks Based on Multimodal Data by Yuhang Dong, Zhengfeng Shi, Junsheng Yao, Li Zhang, Yongkang Chen, Junyan Jia

“…Furthermore, to optimize model performance, different feature selection algorithms were evaluated. …”
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Robust, fully-automated assessment of cerebral perivascular spaces and white matter lesions: a multicentre MRI longitudinal study of their evolution and association with risk of de... by Giuseppe Barisano, Michael Iv, Jeiran Choupan, Melanie Hayden-Gephart, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Enchi Liu, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Danielle Harvey, Michael Donohue, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCarli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, Nigel J. Cairns, Erin Householder, Lisa Taylor Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Faber Kelley, Sungeun Kim, Kwangsik Nho, Zaven Kachaturian, Richard Frank, Peter J. Snyder, Susan Molchan, Jeffrey Kaye, Joseph Quinn, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Ronald Petersen, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva Meyer, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, John C. Morris, Maria Carroll, Sue Leon, Erin Householder, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, Randall Griffith, David Clark, David Geld-macher, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Leyla deToledo-Morrell, Raj C. Shah, Ranjan Duara, Daniel Varon, Maria T. Greig, Peggy Roberts, Marilyn Albert, Chiadi Onyike, Daniel D’Agostino, Stephanie Kielb, James E. Galvin, Dana M. Pogorelec, Brittany Cerbone, Christina A. Michel, Henry Rusinek, Mony J. de Leon, Lidia Glodzik, Susan De Santi, P. Murali Doraiswamy, Jeffrey R. Petrella, Terence Z. Wong, Steven E. Arnold, Jason H. Karlawish, David Wolk, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Ruth A. Mulnard, Gaby Thai, Catherine Mc Adams Ortiz, Kyle Womack, Dana Mathews, Mary Quiceno, Ramon Diaz Arrastia, Richard King, Myron Weiner, Kristen Martin Cook, Michael DeVous, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Heather S. Anderson, Russell H. Swerdlow, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R. Graff Radford, Francine Parfitt, Tracy Kendall, Heather Johnson, Martin R. Farlow, AnnMarie Hake, Brandy R. Matthews, Scott Herring, Cynthia Hunt, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Howard Feldman, Benita Mudge, Michele Assaly, Andrew Kertesz, John Rogers, Dick Trost, Charles Bernick, Donna Munic, Diana Kerwin, Marek Marsel Mesulam, Kristine Lipowski, Chuang Kuo Wu, Nancy Johnson, Carl Sadowsky, Walter Martinez, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Meghan Frey, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Leon Hudson, Evan Fletcher, Owen Carmichael, John Olichney, Charles DeCarli, Smita Kittur, Michael Borrie, T.Y. Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Steven G. Potkin, Adrian Preda, Dana Nguyen, Pierre Tariot, Adam Fleisher, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Anahita Adeli, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Robert B. Santulli, Tamar J. Kitzmiller, Eben S. Schwartz, Kaycee M. Sink, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Henry Querfurth, Geoffrey Tremont, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, Jacobo Mintzer, Kenneth Spicer, David Bachman, Elizabeth Finger, Stephen Pasternak, Irina Rachinsky, John Rogers, Andrew Kertesz, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Laura L. Boles Ponto, Hyungsub Shim, Karen Elizabeth Smith, Norman Relkin, Gloria Chaing, Lisa Raudin, Amanda Smith, Kristin Fargher, Balebail Ashok Raj

“…Interpretation: These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia. …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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Debris-covered glaciers mapping based on machine learning and multi-source satellite images over Eastern Pamir by Aamir Feroz, Shuang Liang, Gunayu Li, Xinwu Li, Zahid Ur Rahman, Bojin Yang

“…Conventional glacier mapping techniques often misclassify debris-covered areas due to their spectral similarity to the surrounding terrain, making this work crucial in addressing these limitations. To improve the accuracy of recognition between debris-covered glaciers and non-glaciated areas by capitalizing on the strengths of multiple machine-learning algorithms and diverse data sources. …”
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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering new opportunities to enhance diagnostic accuracy, personalize treatment plans, and improve service delivery. This review provides a comprehensive overview of the current applications and future potential of AI in ophthalmology. …”
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Computer vision based automatic evaluation method of Y2O3 steel coating performance with SEM image by Jianhong Zhao, Huamin Yang, Yi Sui

“…By leveraging advanced computer vision algorithms, specifically a suitable model for long-term dendritic solidifications named Tang Rui Detect (TRD), the method achieves efficient and accurate detection and quantification of microstructure features. …”
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An intelligible AI-driven decision support system for poststroke mobility assessment by Jin Cheng Liaw, Dominik Raab, Malte Weber, Mario Siebler, Harald Hefter, Dörte Zietz, Marcus Jäger, Andrés Kecskeméthy, Francisco Geu Flores

“…Results: The models yielded good to very good (Cohen) coefficients of determination. …”
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