Verifying the Effects of the Grey Level Co-Occurrence Matrix and Topographic–Hydrologic Features on Automatic Gully Extraction in Dexiang Town, Bayan County, China by Zhuo Chen, Tao Liu

“…Erosion gullies can reduce arable land area and decrease agricultural machinery efficiency; therefore, automatic gully extraction on a regional scale should be one of the preconditions of gully control and land management. The purpose of this study is to compare the effects of the grey level co-occurrence matrix (GLCM) and topographic–hydrologic features on automatic gully extraction and guide future practices in adjacent regions. …”
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Application of artificial neural networks in the drilling processes: Can equivalent circulation density be estimated prior to drilling? by Husam H. Alkinani, Abo Taleb T. Al-Hameedi, Shari Dunn-Norman, David Lian

“…Once ECD is recognized, the crucial drilling variables impact ECD can be modified to control ECD within the acceptable ranges. Data from over 2000 wells collected worldwide were used in this study to create an ANN to predict ECD prior to drilling. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

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Identification of Changing Lower Limb Neuromuscular Activation in Parkinson’s Disease during Treadmill Gait with and without Levodopa Using a Nonlinear Analysis Index by Amir Pourmoghaddam, Marius Dettmer, Daniel P. O’Connor, William H. Paloski, Charles S. Layne

“…Analysis of electromyographic (EMG) data is a cornerstone of research related to motor control in Parkinson’s disease. Nonlinear EMG analysis tools have shown to be valuable, but analysis is often complex and interpretation of the data may be difficult. …”
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Machine learning models for the prediction of preclinical coal workers’ pneumoconiosis: integrating CT radiomics and occupational health surveillance records by Yankun Ma, Fengtao Cui, Yulong Yao, Fuhai Shen, Hongyi Qin, Bing Li, Yan Wang

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Towards rigorous dataset quality standards for deep learning tasks in precision agriculture: A case study exploration by A. Carraro, G. Saurio, F. Marinello

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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…To screen for hub genes associated with OA, a combination of 10 machine learning algorithms and 113 algorithm compositions was integrated. …”
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Effectiveness of an electronic clinical decision support system in improving the management of childhood illness in primary care in rural Nigeria: an observational study by Marek Kwiatkowski, Rodolfo Rossi, Torsten Schmitz, Fenella Beynon, Capucine Musard, Marco Landi, Daniel Ishaya, Jeremiah Zira, Muazu Muazu, Camille Renner, Edwin Emmanuel, Solomon Gideon Bulus

“…Objectives To evaluate the impact of ALgorithm for the MANAgement of CHildhood illness (‘ALMANACH’), a digital clinical decision support system (CDSS) based on the Integrated Management of Childhood Illness, on health and quality of care outcomes for sick children attending primary healthcare (PHC) facilities.Design Observational study, comparing outcomes of children attending facilities implementing ALMANACH with control facilities not yet implementing ALMANACH.Setting PHC facilities in Adamawa State, North-Eastern Nigeria.Participants Children 2–59 months presenting with an acute illness. …”
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Evolving rifampicin and isoniazid mono-resistance in a high multidrug-resistant and extensively drug-resistant tuberculosis region: a retrospective data analysis by Koleka Mlisana, Nomonde Ritta Mvelase, Yusentha Balakrishna, Keeren Lutchminarain

“…This study assessed the changes in resistance levels in culture confirmed Mycobacterium tuberculosis (MTB) in the highest burdened province of South Africa during a period where major changes in diagnostic algorithm were implemented.Setting This study was conducted at the central academic laboratory of the KwaZulu-Natal province of South Africa.Participants We analysed data for all MTB cultures performed in the KwaZulu-Natal province between 2011 and 2014. …”
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Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis by Lu Xing, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu, Hong Shu

“…GSE13355, GSE14905, and GSE73894 were collected from the gene expression omnibus (GEO) database. …”
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The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

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Depression Recognition Using Daily Wearable-Derived Physiological Data by Xinyu Shui, Hao Xu, Shuping Tan, Dan Zhang

“…For comparison, we also utilized data from fifty-eight matched healthy controls from a publicly available dataset, collected using the same devices over equivalent durations. …”
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Constructing a predictive model for acute mastitis in lactating women based on machine learning by Liujing Zhu, Zuyan Huang, Yan Chen, Guangqiu Li, Liwen Liu

“…This study employed a retrospective case-control study approach and collected relevant data from 369 patients with acute mastitis and 447 healthy controls. …”
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Energy Optimisation of Industrial Limestone Grinding Using ANN by Dagmara Kołodziej, Patryk Bałazy, Paweł Knap, Krzysztof Lalik, Damian Krawczykowski

“…In the next phase, black-box optimisation was performed using Bayesian and genetic algorithms to identify optimal mill operating settings. …”
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Pharmaceutical care as the ultimate goal of the мodern pharmacist formation by O. V. Kraydashenko, О. O. Svintozelskyi, A. V. Sarzhevska, T. O. Samura, M. V. Shevchenko

“…During the practical training students should be familiar with the basics of deontology and the ethics of communication with pharmacies visitors; acquire skills of medicinal history collecting. Students are expected to acquire skills of choosing the optimal OTC medicine for a concrete patient and use to practice the algorithm of the distribution patients who need and do not need doctor consultation. …”
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Interpersonal counselling for adolescent depression delivered by youth mental health workers without core professional training: the ICALM feasibility RCT by Jon Wilson, Viktoria Cestaro, Eirini Charami-Roupa, Timothy Clarke, Aoife Dunne, Brioney Gee, Sharon Jarrett, Thando Katangwe-Chigamba, Andrew Laphan, Susie McIvor, Richard Meiser-Stedman, Jamie Murdoch, Thomas Rhodes, Carys Seeley, Lee Shepstone, David Turner, Paul Wilkinson

“…Mixed-methods process data were collected to understand how the intervention was implemented across settings, explore acceptability and monitor contamination. …”
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Cervical cancer prediction using machine learning models based on routine blood analysis by Jie Su, Hui Lu, Ruihuan Zhang, Na Cui, Chao Chen, Qin Si, Biao Song

“…In this restrospective study, medical records of patients from 2013 to 2023 were collected. A total of 2,503 patients diagnosed with CC were included in the case group, while the control group was composed of 3,794 patients without apparent signs of the disease, which included women with other gynecological conditions as well as healthy individuals undergoing routine check-ups. …”
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Development and validation of interpretable machine learning models for postoperative pneumonia prediction by Bingbing Xiang, Yiran Liu, Shulan Jiao, Wensheng Zhang, Shun Wang, Mingliang Yi

“…This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods.ObjectiveOur study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. By evaluating the performance differences among these machine learning models, this study aims to assist clinicians in early prediction and diagnosis of POP, providing optimal interventions and treatments.MethodsRetrospective data from electronic medical records was collected for 264 patients diagnosed with postoperative pneumonia and 264 healthy control surgical patients. …”
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TKEO-Enhanced Machine Learning for Classification of Bearing Faults in Predictive Maintenance by Xuanbai Yu, Olivier Caspary

“…These findings offer new insights to support reliable predictive maintenance in industrial settings and provide a new perspective for future research into active vibration control, where vibration signal analysis, feature extraction, and mathematical modeling play key roles in optimizing control algorithms and enhancing the efficiency of adaptive control systems.…”
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Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

“…Trained using the light gradient boosting machine algorithm on clinical data from 1,927 KD cases and 45,274 febrile controls, KDpredictor achieved strong performance metrics (auROC: 95.7%, auPRC: 72.4%, recall: 0.89) on a reserved test set, outperforming previous models by at least 3% in auROC and 39.3% in auPRC. …”
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