Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke by Yi Cao, Yi Cao, Haipeng Deng, Shaoyun Liu, Xi Zeng, Yangyang Gou, Weiting Zhang, Yixinyuan Li, Hua Yang, Min Peng

“…Model performance was compared using Delong's test or Bootstrap test, while sensitivity, specificity, accuracy, precision, recall, and F1-score evaluated predictive efficacy. …”
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Management and outcome of whole-spine epidural abscesses – institutional case series and systematic review by Erik Schulz, Linda Bättig, Felix C. Stengel, Lorenzo Bertulli, Nader Hejrati, Maximilian Wegener, Carol Strahm, Benjamin Martens, Martin N. Stienen, Stefan Motov

“…Research question: What are the optimal management strategies for WSEAs based on current evidence? …”
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Machine Learning-Based Summer Crops Mapping Using Sentinel-1 and Sentinel-2 Images by Saeideh Maleki, Nicolas Baghdadi, Hassan Bazzi, Cassio Fraga Dantas, Dino Ienco, Yasser Nasrallah, Sami Najem

“…Additionally, the InceptionTime classifier, specifically designed for time series data, was tested exclusively with time series datasets to compare its performance against the three general machine learning algorithms (RF, XGBoost, and MLP). The results showed that XGBoost outperformed RF and MLP in classifying the three crops. …”
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Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020 by Luis Gabriel Cuervo, Carmen Juliana Villamizar, Daniel Cuervo, Pablo Zapata, Maria B. Ospina, Sara Marcela Valencia, Alfredo Polo, Ángela Suárez, Maria O. Bula, J. Jaime Miranda, Gynna Millan, Diana Elizabeth Cuervo, Nancy J. Owens, Felipe Piquero, Janet Hatcher-Roberts, Gabriel Dario Paredes, María Fernanda Navarro, Ingrid Liliana Minotta, Carmen Palta, Eliana Martínez-Herrera, Ciro Jaramillo, on behalf of the AMORE Project Collaboration

“…The platform integrates open data, including the location of radiotherapy services, the disaggregated sociodemographic microdata for the population and places of residence, and big data for travel times from Google Distance Matrix API. We used genetic algorithms to identify optimal locations for new services. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…Abstract Background Metastatic spinal disease often leads to significant morbidity, and accurate prediction of postoperative outcomes can help optimize patient management and resource allocation. …”
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Interpretable Machine Learning for Legume Yield Prediction Using Satellite Remote Sensing Data by Theodoros Petropoulos, Lefteris Benos, Remigio Berruto, Gabriele Miserendino, Vasso Marinoudi, Patrizia Busato, Chrysostomos Zisis, Dionysis Bochtis

“…Accurate crop yield prediction is vital towards optimizing agricultural productivity. Machine Learning (ML) has shown promise in this field; however, its application to legume crops, especially to lupin, remains limited, while many models lack interpretability, hindering real-world adoption. …”
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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Modeling Habitat Suitability of Anser Anser in Iran by Fatemeh Biglari Quchan Atiq, Azita Farashi, Mitra Shariati Najafabadi

“…The findings from evaluating the algorithms used in modeling the habitat types of the Anser anser species reveal that the biomod software package has a high ability to predict the optimal habitats of this species. …”
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Evaluating and Forecasting the Probability of Lightning Occurrence in Rasht City by Afsaneh Ghasemi, Jamil Amanollahi

“…According to the results of the models, the probability of lightning occurrence is higher in the months of May, June and July than in other months and the rate of occurrence from spring to winter has a decreasing trend, while in winter it is at least. CHAID tree with a specificity rate of 0.794 and a minimum false positive rate of 0.205 and the SVM model with a correct prediction of 0.773 and an error rate of 0.475 and precision of 0.855 have optimum performance compared with other models. …”
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Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…Although a KM program is extremely important for the preservation and optimized utilization of such archives, its systematic implementation in Iran has not yet been comprehensively examined. …”
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