Costs of testing sick children in primary care with pulse oximetry: Evidence from four countries, both with and without electronic clinical decision support. by Susan Horton, Ulrich Adombi, Fenella Beynon, Mira Emmanuel-Fabula, Tara Herrick, Sandeep Kumar, Suzan Makawia, Mercy Mugo, Michael Onah, Michael Ruffo, Shally Awasthi, Maymouna Ba, Leah F Bohle, Silvia Cicconi, Hélène Langet, Papa Moctar Faye, Honorati Masanja, Andolo Miheso, Deusdedit Mjungu, James Machoki M'Imunya, Ousmane Ndiaye, Kovid Sharma, Valérie D'Acremont, Kaspar Wyss, TIMCI Collaborator Group

“…Adding clinical decision support algorithms (CDSA) can improve adherence to Integrated Management of Childhood Illness guidelines. …”
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Residential Electricity Load Model Construction in District Scale by Jieyan XU, Wenyang XU, Yuan CHU, Yuan JIN, Xuyuan KANG, Zheng CHEN

“…To this end, this study proposes a method integrating auto-encoding and neighbor clustering algorithms for data outlier detection for data with high-dimensional characteristics at the spatial and temporal scales. …”
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Polypharmacy driven synergistic toxicities in elderly breast cancer chemotherapy drug management and adverse drug reactions: a mini review by Xiran Wang, Xiran Wang, Jin Yang, Jin Yang, Jieying Zhang, Jieying Zhang, Hong Yang, Hong Yang

“…Pharmacist-led reconciliation coupled with algorithmic deprescribing removes ≥1 potentially inappropriate medication in 80% of elders, while electronic rPDDI alerting and DPYD/CYP2D6 genotyping halve severe events without sacrificing efficacy. …”
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High-levels of acquired drug resistance in adult patients failing first-line antiretroviral therapy in a rural HIV treatment programme in KwaZulu-Natal, South Africa. by Justen Manasa, Richard J Lessells, Andrew Skingsley, Kevindra K Naidu, Marie-Louise Newell, Nuala McGrath, Tulio de Oliveira, Southern African Treatment and Resistance Network

“…Sequences were analysed and genotypic susceptibility scores (GSS) for standard second-line regimens were calculated using the Stanford HIVDB 6.0.5 algorithms.<h4>Results</h4>A total of 222 adults were successfully genotyped for HIV drug resistance between December 2010 and March 2012. …”
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Optimum Combination of Spectral Variables for Crop Mapping in Heterogeneous Landscapes based on Sentinel-2 Time Series and Machine Learning by J. G. de Oliveira Júnior, J. C. D. M. Esquerdo, J. C. D. M. Esquerdo, R. A. C. Lamparelli, R. A. C. Lamparelli

“…Subsequently, the variables that showed the highest statistical correlation between each other were used in the spectro-temporal classification process, using the Random Forest, TempCNN, and LightTAE algorithms, following three different strategies: C1 (ALL), C2 (BE + IV _{(Red Edge)}) and C3 (BE + IV _{(without Red Edge)}), where ALL &ndash; All variables; BE &ndash; Spectral Bands; IV &ndash; Vegetation Indices. …”
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To explore the molecular mechanisms and shared genetic characteristics of rheumatoid arthritis and cervical cancer based on multiple omics and clinical samples by Xifeng Xu, Yujie Huang, Wu Wei, Zhong Lin, Yongjin Luo, Kaiyi Meng

“…Single-cell enrichment scores were calculated using RA-specific transcriptome differentially expressed genes, and prognostic models were developed using 10 machine learning algorithms to assess cervical cancer differential gene expression associated with RA scores. …”
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Lightweight and robust ship detection method driven by self-attention mechanism by Feng MA, Zihui SHI, Jie SUN, Chen CHEN, Xianbin MAO, Xinping YAN

“…During testing, the proposed method demonstrates superior overall ship detection performance compared to other algorithms, with a mAP of 92.9%, a precision rate of 92.1%, and a parameter size of 35 366 310. …”
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Machine learning for asphaltene polarizability: Evaluating molecular descriptors by Arun K. Sharma, Owen McMillan, Selsela Arsala, Supreet Gandhok, Rylend Young

“…The Wolfram Language’s Predict function evaluated multiple machine learning algorithms—including Random Forest, Decision Tree, Gradient Boosted Trees, Nearest Neighbors, Linear Regression, Gaussian Process, and Neural Network—through an automated model selection process, serving as an AutoML framework. …”
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Application of Internet Hospitals in the Disease Management of Patients With Ulcerative Colitis: Retrospective Study by Tianzhi Yu, Wanyu Li, Yingchun Liu, Chunjie Jin, Zimin Wang, Hailong Cao

“…Intelligent diagnosis refers to the use of artificial intelligence–driven algorithms to analyze patient-reported symptoms, generate diagnostic probabilities, and provide treatment recommendations through interactive tools. …”
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Downscaling Satellite Night-Time Light Imagery While Addressing the Blooming Effect by Nikolaos Tziokas, Ce Zhang, Alexandros Tziokas, Qunming Wang, Peter M. Atkinson

“…We compared several image fusion algorithms for downscaling while reducing the blooming effect. …”
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Integrating Machine Learning and Geospatial Data for Mapping Socioeconomic Vulnerability to Urban Natural Hazard by Esaie Dufitimana, Paterne Gahungu, Ernest Uwayezu, Emmy Mugisha, Jean Pierre Bizimana

“…We utilized a variety of data sources, such as demographic, environmental, and remotely sensing datasets, applying machine learning algorithms like Multilayer Perceptron (MLP), Random Forest, Support Vector Machine (SVM), and XGBoost. …”
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A Comparative Analysis of Machine Learning and Pedotransfer Functions Under Varying Data Availability in Two Greek Regions by Panagiotis Tziachris, Panagiota Louka, Eirini Metaxa, Miltiadis Iatrou, Konstantinos Tsiouplakis

“…The current study evaluates the performance of pedotransfer functions (PTFs) and machine learning (ML) algorithms in predicting the soil bulk density (BD) across two distinct regions in Greece—Kozani and Veroia—using both limited and extended sets of soil parameters. …”
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Practical Recommendations for Artificial Intelligence and Machine Learning in Antimicrobial Stewardship for Africa by Tafadzwa Dzinamarira, Elliot Mbunge, Claire Steiner, Enos Moyo, Adewale Akinjeji, Kaunda Yamba, Loveday Mwila, Claude Mambo Muvunyi

“…Effective policy development is equally essential to establishing regulatory frameworks that ensure data security, algorithmic fairness, and ethical AI use. This comprehensive approach will not only improve the deployment of AI systems but also address the underlying issues that exacerbate AMR, such as unauthorized antibiotic sales and inadequate enforcement of guidelines. …”
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Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…AI-driven technologies, including deep learning algorithms and machine learning models, are emerging as valuable tools in cervical cancer detection, risk assessment, and treatment planning. …”
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Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method by Chia-Hao Shih, Elyssa Charlotte Feuer, Ben Kurzion, Kevin Xu, Hong Xie, Stephen R. Grider, Xin Wang

“…The performance of the CART model was benchmarked against two of the most powerful and widely used machine learning algorithms in the field, Random Forest (RF) and Gradient Boosting (GB) models.Results: The CART model, which incorporates just three critical questions from established assessments, predicted PTSD development with performance closely matched to that of the RF and GB models. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…Methodologically, the study used CNN algorithms optimised by Bayesian techniques for the prediction of eight water quality indices, coupled with SHAPley Additive exPlanations (SHAP) analysis under XAI to interpret the complex decision-making processes of these models. …”
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Simple energy detector for two-stage classification for antidrone systems by Zurovac Snežana, Petrović Nikola, Joksimović Vasilija, Pokrajac Ivan, Mikanović Darko, Sazdić-Jotić Boban

“…Furthermore, we conducted a comparative analysis of different deep learning algorithms at the outset of twostage classification, which is a potential basis for adopting this approach.…”
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Disinformation in the Digital Age: Climate Change, Media Dynamics, and Strategies for Resilience by Andrea Tomassi, Andrea Falegnami, Elpidio Romano

“…Our findings indicate that social media algorithms and user dynamics can amplify false scientific claims, as seen in case studies of viral misinformation campaigns on vaccines and climate change. …”
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Exploration of shared pathogenic factors and causative genes in early-stage endometrial cancer and osteoarthritis by Yiyun Bai, Sang Luo, Ruzhen Shuai, Xiaomei Zhang, Liwei Yuan, Dan Liu

“…Genes with diagnostic value were identified using multiple machine learning algorithms to construct EC prediction models and evaluate their performance. …”
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Bayesian Model Prediction for Breast Cancer Survival: A Retrospective Analysis by Islam Bani Mohammad, Muayyad M. Ahmad

“…Objective: Over the recent years, machine learning (ML) models have been increasingly used in predicting breast cancer survival because of improvements in ML algorithms. However, cancer researchers still face a significant challenge in accurately predicting breast cancer patients’ survival rates. …”
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