Prevalence, types, risk factors and clinical correlates of anaemia in older people in a rural Ugandan population. by Joseph O Mugisha, Kathy Baisley, Gershim Asiki, Janet Seeley, Hannah Kuper

“…Clinicians should consider screening older people with HIV or malaria for anaemia. …”
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High-throughput discovery of genetic determinants of circadian misalignment. by Tao Zhang, Pancheng Xie, Yingying Dong, Zhiwei Liu, Fei Zhou, Dejing Pan, Zhengyun Huang, Qiaocheng Zhai, Yue Gu, Qingyu Wu, Nobuhiko Tanaka, Yuichi Obata, Allan Bradley, Christopher J Lelliott, Sanger Institute Mouse Genetics Project, Lauryl M J Nutter, Colin McKerlie, Ann M Flenniken, Marie-France Champy, Tania Sorg, Yann Herault, Martin Hrabe De Angelis, Valerie Gailus Durner, Ann-Marie Mallon, Steve D M Brown, Terry Meehan, Helen E Parkinson, Damian Smedley, K C Kent Lloyd, Jun Yan, Xiang Gao, Je Kyung Seong, Chi-Kuang Leo Wang, Radislav Sedlacek, Yi Liu, Jan Rozman, Ling Yang, Ying Xu

“…We developed a machine learning algorithm to quantify these two parameters in our misalignment screen (SyncScreener) with existing datasets and used it to screen 750 mutant mouse lines from five IMPC phenotyping centres. …”
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Atrial fibrillation with thrombotic complications. Justification of the diagnosis and treatment regimen according to evidence-based medicine (clinical case) by L.O. Martymianova, E.P. Kamenska, A.O. Bulyha, K.О. Serdyuk

“…Diagnosis and systematic screening of AF, as well as timely assessment of stroke risk, are of paramount importance for the prognosis of patients, especially in older age groups. …”
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Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network by Gang Zhao, Changyu Han, Zhongxiang Yu, Zhipan Li, Guoao Yu, Hongmei Zhang, Dadong Zhao, Zhengyi Jiang

“…The single-stage object detection algorithm YOLOv5 (You Only Look Once) based on convolutional neural network model calculation is used, the scale detection layer and positioning loss function of the YOLOv5 algorithm are improved and optimized, and the improved YOLOv5 algorithm is used for experiments. …”
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Research Progress and Prospect of Green Infrastructure with Public Health Promotion Function by Tongyu LI, Junyi LIXU, Binxia XUE, Yan (USA) SONG

“…To manage the multidimensionality of GI research, cluster analysis is performed using a Word2Vec model combined with a K-means algorithm to integrate different GI forms into a coherent classification system.ResultsThe results show that GI can be clearly divided into different categories, such as urban green spaces and parks, high-interaction spaces, trees in built-up areas, water management and biofiltration systems, community and residential greening, green roofs and facades, linear green networks, and broader macro-GI strategies. …”
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An incremental data-driven approach for carbon emission prediction and optimization of heat treatment processes by Qian Yi, Xin Wu, Junkang Zhuo, Congbo Li, Chuanjiang Li, Huajun Cao

“…Using life cycle assessment (LCA) theory, carbon emission sources are accurately analyzed and quantified, and a full life cycle carbon emission model is established. The key process parameters affecting part performance and carbon emission were screened through mechanism analysis, and the incremental data were fused by the Elasticity Weight Consolidation (EWC) algorithm to establish an EWC-BPNN heat treatment carbon emission prediction model. …”
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Structural strength optimization design of ultra-high-pressure and ultra-wear-resistant pneumatic ball valve opened and closed at large explosion instantaneously using finite eleme... by Xianmei Liu, Mingcun Zhang

“…By building an ultra-high pressure burst test bench, this paper combines strain gauges and high-speed cameras to verify the accuracy of the model and corrects the simulation boundary conditions based on the Kalman filter algorithm. …”
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Recent Trends and Advances in Utilizing Digital Image Processing for Crop Nitrogen Management by Bhashitha Konara, Manokararajah Krishnapillai, Lakshman Galagedara

“…In addition, image data using more variables as model inputs, including agriculture sensors and meteorological data, have increased prediction accuracy. …”
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Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review by Suhila Sawesi, Arya Jadhav, Bushra Rashrash

“…MethodsUsing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), and Prediction model Risk of Bias Assessment Tool (PROBAST) tools, we conducted a comprehensive review of studies applying ML and DL models for leptospirosis detection and prediction, examining algorithm performance, data sources, and validation approaches. …”
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Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk by Ji-Eun Song, Ji Young Jang, Kyung Nam Kang, Ji Soo Jung, Chul Woo Kim, Ah Sol Kim

“…Breast cancer risk scores for each Breast Imaging-Reporting and Data System (BI-RADS) category in multi-microRNA analysis were analyzed to examine the correlation between breast cancer risk scores and mammography categories. We generated two models using two classification algorithms, SVM and GLM, with a combination of four miRNA biomarkers showing high performance and sensitivities of 84.5% and 82.1%, a specificity of 85%, and areas under the curve (AUCs) of 0.967 and 0.965, respectively, which showed consistent performance across all stages of breast cancer and patient ages. …”
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Nanomaterial isolated extracellular vesicles enable high precision identification of tumor biomarkers for pancreatic cancer liquid biopsy by Zachary F. Greenberg, Samantha Ali, Andrew Brock, Jinmai Jiang, Thomas D. Schmittgen, Song Han, Steven J. Hughes, Kiley S. Graim, Mei He

“…Through modelling the ATP6V0B cycling threshold, we reported 3 models with AUCs between 0.86 and 0.88, showcasing an enabling and clinically translatable liquid biopsy approach for early detection of pancreatic cancer using circulating EVs. …”
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Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis by Hang Chen, Biao Wu, Biao Wu, Kunyu Guan, Liang Chen, Kangjie Chai, Maoji Ying, Dazhi Li, Weicheng Zhao

“…Through further differential analysis and screening using machine learning algorithms, APLNR, PCDH12, PODXL, SLC40A1, TM4SF18, and TNFRSF25 were identified as key diagnostic genes for atherosclerosis. …”
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Estimation of the aboveground carbon stocks based on tree species identification in Saihanba plantation forest by Ao Zhang, Xiaohong Wang, Xin Gu, Xiangyao Xu, Xintong Gao, Linlin Jiao

“…The results were shown that: 1) The identification effect of Scheme IV, as ascertained by screening three types of effective feature vectors based on the random forest algorithm, was the most effective, with an overall accuracy (OA) and kappa coefficient of 89.7% and 0.863, respectively. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Traditional invasive diagnostic methods are costly, inconvenient, and unsuitable for large-scale screening. Developing a non-invasive, accurate prediction model is clinically significant for early MetS detection and prevention. …”
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U-shaped relationship between frailty and non-HDL-cholesterol in the elderly: a cross-sectional study by Yu Pan, Yan Yuan, Juan Yang, Zhu Qing Feng, Xue Yin Tang, Yi Jiang, Gui Ming Hu, Jiang Chuan Dong

“…The variables underwent screening through Least Absolute Shrinkage and Selection Operator (LASSO) regression, univariate logistic regression, and Light Gradient Boosting Machine (LightGBM), with models developed through multivariate logistic regression and the LightGBM algorithm. …”
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Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech by Julianna Olah, Win Lee Edwin Wong, Atta-ul Raheem Rana Chaudhry, Omar Mena, Sunny X. Tang

“…Linguistic and paralinguistic features were extracted and ensemble learning algorithms (e.g., XGBoost) were used to train models. …”
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Enhanced thyroid nodule detection and diagnosis: a mobile-optimized DeepLabV3+ approach for clinical deployments by Changan Yang, Muhammad Awais Ashraf, Mudassar Riaz, Pascal Umwanzavugaye, Kavimbi Chipusu, Hongyuan Huang, Yueqin Xu

“…A high IoU value in medical imaging analysis reflects the model’s ability to accurately delineate object boundaries.ConclusionDeepLabV3+ represents a significant advancement in thyroid nodule segmentation, particularly for thyroid cancer screening and diagnosis. …”
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Prevention of Cardiometabolic Syndrome in Children and Adolescents Using Machine Learning and Noninvasive Factors: The CASPIAN-V Study by Hamid Reza Marateb, Mahsa Mansourian, Amirhossein Koochekian, Mehdi Shirzadi, Shadi Zamani, Marjan Mansourian, Miquel Angel Mañanas, Roya Kelishadi

“…We applied the XGBoost algorithm to analyze key noninvasive variables, including self-rated health, sunlight exposure, screen time, consanguinity, healthy and unhealthy dietary habits, discretionary salt and sugar consumption, birthweight, and birth order, father and mother education, oral hygiene behavior, and family history of dyslipidemia, obesity, hypertension, and diabetes using five-fold cross-validation. …”
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Health-Related Quality-of-Life Utility Values in Adults With Late-Onset Pompe Disease: Analyses of EQ-5D Data From the PROPEL Clinical Trial by Alison Griffiths, Simon Shohet, Neil Johnson, Alasdair MacCulloch

“…In PROPEL, EQ-5D-5L values were assessed at screening and at weeks 12, 26, 38, and 52. EQ-5D-5L utility values were mapped to EQ-5D-3L values using the van Hout algorithm as recommended by the EuroQoL and the National Institute of Health and Care Excellence position statement at time of analysis. …”
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Retinal Microvascular Characteristics—Novel Risk Stratification in Cardiovascular Diseases by Alexandra Cristina Rusu, Klara Brînzaniuc, Grigore Tinica, Clément Germanese, Simona Irina Damian, Sofia Mihaela David, Raluca Ozana Chistol

“…This study aims to identify the retinal microvascular features associated with CHDs and evaluate their potential use in a CHD screening algorithm in conjunction with traditional risk factors. …”
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