An IoT-enabled AI system for real-time crop prediction using soil and weather data in precision agriculture by MD Shaifullah Sharafat, Nilavro Das Kabya, Rahimul Islam Emu, Mehrab Uddin Ahmed, Jakaria Chowdhury Onik, Mohammad Aminul Islam, Riasat Khan

“…Several machine learning algorithms, including Random Forest, Gradient Boosting, and Stacking ensembles, as well as deep learning models such as TabNet, were evaluated for crop prediction. …”
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Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC by Ning Wang, Ziyu Xu, Lina Zhang, Lina Zhang, Yanfang Lu, Yanfang Lu, Yanliang Wang, Yanliang Wang, Lei Yan, Lei Yan, Huixia Cao, Huixia Cao, Limeng Wang, Limeng Wang, Fengmin Shao, Fengmin Shao

“…Functional enrichment algorithms, including AUCell, UCell, singscore, ssGSEA, and AddModuleScore, along with hdWGCNA analysis, were used to identify hub genes influencing high FAM of ccRCC. …”
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Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
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Burden of chronic spontaneous urticaria in Italy through healthcare resource utilization and direct costs: a retrospective analysis of real-world using administrative healthcare da... by Giulia Ronconi, Letizia Dondi, Silvia Calabria, Leonardo Dondi, Irene Dell’Anno, Lucia Casoli, Diletta Valsecchi, Ornella Bonavita, Eustachio Nettis, Nello Martini, Carlo Piccinni

“…Conclusions During the first year following the new CSU diagnosis, a lower than recommended antihistamines dispensation while an elevated use of OCS and a low and delayed omalizumab initiation after CSU exacerbation were observed, suggesting the urgent need to optimize treatment management to limit the burden on patients and healthcare systems.…”
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Identification and validation of diagnostic biomarkers and immune cell abundance characteristics in Staphylococcus aureus bloodstream infection by integrative bioinformatics analys... by Junhong Shi, Li Shen, Yanghua Xiao, Cailing Wan, Bingjie Wang, Peiyao Zhou, Jiao Zhang, Weihua Han, Rongrong Hu, Fangyou Yu, Hongxiu Wang

“…Gene expression dataset GSE33341 was optimized as the discovery dataset, which contained samples from human and mice. …”
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Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study by Huiyu Yao, Zixin Cao, Liangfu Huang, Haojie Pan, Xiaomin Xu, Fucai Sun, Xi Ding, Wan Wu

“…Future research should focus on validating these findings in larger cohorts and exploring alternative machine-learning algorithms to improve diagnostic accuracy further.…”
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Resveratrol contributes to NK cell-mediated breast cancer cytotoxicity by upregulating ULBP2 through miR-17-5p downmodulation and activation of MINK1/JNK/c-Jun signaling by Bisha Ding, Jie Li, Jia-Lin Yan, Chun-Yan Jiang, Ling-Bo Qian, Jie Pan

“…Resveratrol (RES) is known for its multiple health benefits, while current understanding of its role in regulating cancer immunogenicity remains limited. …”
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PhA-MOE: Enhancing Hyperspectral Retrievals for Phytoplankton Absorption Using Mixture-of-Experts by Weiwei Wang, Bingqing Liu, Song Gao, Jiang Li, Yueling Zhou, Songyang Zhang, Zhi Ding

“…Traditional methods often fail under these circumstances, while improved machine-learning approaches are hindered by data scarcity, heterogeneity, and noise from data collection. …”
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Molecular subtype of recurrent implantation failure reveals distinct endometrial etiology of female infertility by Jing Yang, Lingtao Yang, Ying Zhou, Fengyang Cao, Hongkun Fang, Huan Ma, Jun Ren, Chunyu Huang, Lianghui Diao, Qiyuan Li, Qionghua Chen

“…A molecular classifier (MetaRIF) was developed using the optimal F-score from 64 combinations of machine learning algorithms. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Comparative data suggest that while both machine learning and deep learning approaches perform well, some deep learning models may offer slight advantages in complex data environments. …”
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Design and Implementation of a Deep Learning-Based Hand Gesture Recognition System for Rehabilitation Internet-of-Things (RIoT) Environments Using MediaPipe by Nurul Hanis Mohd Dhuzuki, Ahmad Anwar Zainuddin, Nur Anis Sofea Kamarul Zaman, Alin Nur Maisarah Ahmad Razmi, Wonderful Shammah Kaitane, Asmarani Ahmad Puzi, Mohd Naqiuddin Johar, Maslina Yazid, Nor Azlin Mohd Nordin, Shahrul Naim Sidek, Hasan Firdaus Mohd Zaki

“…The system's objective is to provide precise, real-time tracking of hand movements, enabling patients to perform exercises at home by maintaining an optimal distance between the camera and hand placement, ensuring ideal room lighting conditions across IoT devices such as mobile phones' front cameras and webcams, while healthcare professionals remotely monitor their progress. …”
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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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