Prion forensics: a multidisciplinary approach to investigate CWD at an illegal deer carcass disposal site by Marc D. Schwabenlander, Jason C. Bartz, Michelle Carstensen, Alberto Fameli, Linda Glaser, Roxanne J. Larsen, Manci Li, Rachel L. Shoemaker, Gage Rowden, Suzanne Stone, W. David Walter, Tiffany M. Wolf, Peter A. Larsen

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Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score by Mike Nsubuga, Timothy Mwanje Kintu, Helen Please, Kelsey Stewart, Sergio M. Navarro

“…Methods Data from 4,109 trauma patients at Soroti Regional Referral Hospital, a rural hospital in Uganda, were used to train and evaluate four ML models: Logistic Regression (LR), Random Forest (RF), Gradient Boosting (GB), and Support Vector Machine (SVM). …”
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On-Farm Experimentation with Improved Maize Seed and Soil Amendments in Southern Ghana: Productivity Effects in Small Holder Farms by E. Marfo-Ahenkora, K. J. Taah, E. Owusu Danquah, E. Asare-Bediako

“…To contribute to addressing these challenges in maize production, two on-farm experiments were conducted each in the semi deciduous forest and coastal savannah agroecological zones (AEZs) of Ghana during the major and minor cropping seasons of 2017. …”
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Predicting Solar Energetic Particle Events with Time Series Shapelets by Omar Bahri, Peiyu Li, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi

“…Then, we use our proposed approach to mine shapelets and make predictions using a random forest classifier. We demonstrate that our approach rivals state-of-the-art SEP prediction, offering superior interpretability and the ability to predict SEP events before their parent eruptive flares.…”
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A dataset from the Cryptogamia-Lichenes section of the Herbarium Universitatis Taurinensis (TO) by Rosanna Piervittori, Deborah Isocrono, Enrica Matteucci, Mariagrazia Morando, Luca Dessì, Laura Guglielmone, Heimo Rainer, Stefano Martellos, Andrea Moro, Pier Luigi Nimis, Matteo Conti, Sergio Enrico Favero-Longo

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Impact of tourist and recreational activities on the indicators of soil-ecological monitoring of the adjacent territory of Lake Teletskoe (Altai Mountains) by Olga A. Elchininova

“…Because of the tourist activities in the coastal zone of the mountain-forest belt of Lake Teletskoe, a developed path network transforming its natural ecosystems appeared. …”
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Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes by Liu Yang, Li Du, Yuanyuan Ge, Muhui Ou, Wanyan Huang, Xianmei Wang

“…These nine factors were employed to establish stepwise regression (SR), random forest (RF), naïve Bayes (NB), decision trees (DT), and artificial neutron network (ANN), whose performances were evaluated in terms of accuracy, kappa, F1, receiver operating characteristic, precision recall curve, etc. …”
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The Impact and Mechanism of New-Type Urbanization on High-Quality Forestry Development: A Case Study of the Yellow River Basin in China by Longbo Ma, Qian Wang, Yiqi Zhu, Zujun Liu

“…The Paris Agreement emphasizes the critical role of forests in addressing climate change and ecological protection. …”
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Using selective NIR wavelengths in portable devices to evaluate the chemical composition of cattle feeds by Lorenzo Serva, Luisa Magrin, Giovanni Chillemi, Giorgio Marchesini, Daniele Pietrucci, Francesco Renzi, Riccardo Valentini, Igino Andrighetto, Marco Milanesi

“…This was achieved by evaluating various cattle rations and silages (including rations for cows and bulls and grass and corn silage), where we selected the most significant wavelengths for fibre characterisation using the Random Forest (Boruta) algorithm. The number of identified features varied based on the spectral pre-treatments applied or the use of a batch effect reduction algorithm (ComBat function). …”
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Risk Factors for Contralateral Occult Papillary Thyroid Carcinoma in Patients with Clinical Unilateral Papillary Thyroid Carcinoma: A Case-Control Study by Liu Yihao, Li Shuo, Xi Pu, Wang Zipeng, Sun Hanlin, Chang Qungang, Wang Yongfei, Yin Detao

“…Univariate and multivariate logistic regression analyses were conducted to assess the association between COPTC and clinical-pathological characteristics, as well as the relation between the diameter of the occult lesions and predictors. The forest plot was plotted to visualize the prediction factors from the output of the multivariate regression analysis. …”
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Lighting Spectrum Optimization With Deep Learning for Moss Species Classification by Kenichi Ito, Pauli Falt, Markku Hauta-Kasari, Shigeki Nakauchi

“…Hence, we propose a method for obtaining spectral information on moss in the forest using a deep learning model to train convolutional neural network models while optimizing a suitable light source for moss identification. …”
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Dwarf shrub expansion and loss of lichens distinctly dominate multi-decadal changes in northern boreal understory plant communities by Tuija Maliniemi, Joonatan Lohi, Janne Alahuhta, Karoliina Huusko, Risto Virtanen

“… Northern boreal forests and treelines are particularly sensitive to the current climate change that has already resulted in increased productivity, shrub expansion and up- and northward shifts of species. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…Finally, a hybrid model combining an unsupervised SOM and followed by the supervised Random Forest model returned an accuracy of 83.47% for the training and 80.77% for the test, with Bathymetry, Chlorophyll, and Coarse Sand as key predictive variables. …”
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« Une femme en Côte d’Ivoire, une femme au Burkina Faso » by François Ruf

“…Côte d’Ivoire, with its diversity of forest and savannah regions, and its neighbour to the north, Burkina Faso, are historically linked to the creation and growth of the Ivorian village plantation economy based on the ‘coffee-cocoa’ pairing. …”
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A Dynamic Bayesian Network-Based Real-Time Crash Prediction Model for Urban Elevated Expressway by Xian Liu, Jian Lu, Zeyang Cheng, Xiaochi Ma

“…In this study, Dynamic Bayesian Network (DBN) was the framework of the RTCPM. Random Forest (RF) method was employed to identify the most important variables, which were used to build DBN-based RTCPMs. …”
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Sensitivity assessment and simulation of ecosystem services in response to land use change in arid regions: Empirical evidence from Xinjiang, China by Xiaoyun Li, Chunsheng Wu

“…The expense was the losses of forest land and grassland, with reductions of 5.84% and 4.15%, respectively. …”
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Spatial scales matter in designing buffer zones for coastal protected areas along the East Asian-Australasian Flyway by Roger H. Lee, Ivan H.Y. Kwong, Tom C.H. Li, Paulina P.Y. Wong, Yik-Hei Sung, Yat-Tung Yu

“…By integrating remotely sensed parameters and 3-year monthly waterbird surveys in and around the Mai Po Inner Deep Bay Ramsar Site of Hong Kong, a key stopover of the East Asian Australasian Flyway, we mapped waterbird occurrences for all and different waterbird guilds during winter and summer using random forest models. We found that suitable habitats were predominantly found within protected areas, yet ardeids, large wading birds, ducks and grebes also relied on buffer zones. …”
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Identification of key genes underlying radiosensitivity and radioresistance in endometrial cancer through integrated bioinformatics analysis by Chunhui Wan, Lei Zhang, Ting Yu, Hui Lu, Han Xiao, Juan Du

“…Applied Lasso regression and randomized survival forest model to identify key genes. Performed functional annotation, correlation analysis, and survival analysis on key genes.ResultsKey genes positively correlated with UCEC tumorigenesis-related genes in the radioresistant group. …”
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Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study by Kanika Godani, Vishma Prabhu, Priyanka Gandhi, Ayushi Choudhary, Shubham Darade, Rupal Kathare, Prathiba Hande, Ramesh Venkatesh

“…Six supervised ML models—ANCOVA, Random Forest (RF) regression, K-Nearest Neighbor, Support Vector Machine, Extreme Gradient Boosting, and Lasso regression—were trained using an 80:20 training-to-testing split. …”
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Experimental investigation on fresh, hardened and durability characteristics of partially replaced E-waste plastic concrete: A sustainable concept with machine learning approaches by Md. Hamidul Islam, Zannatun Noor Prova, Md. Habibur Rahman Sobuz, Nusrat Jahan Nijum, Fahim Shahriyar Aditto

“…With high coefficient correlation (R2) values, the linear regression (LR) model predicted mechanical property outcomes more accurately than the random forest (RF) model. The electrical resistivity test showed better results increased range of 239.06 %–478.82 %. …”
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