Artificial intelligence-based prediction of second stage duration in labor: a multicenter retrospective cohort analysisResearch in context by Xiaoqing Huang, Xiaodan Di, Suiwen Lin, Minrong Yao, Suijin Zheng, Shuyi Liu, Wayan Lau, Zhixin Ye, Zilian Wang, Bin Liu

“…After the optimal features selected by recursive feature elimination (RFE) method, four ML algorithms were employed to build the models. The best model would be selected with the predictive performance and interpreted with Shapley Additive exPlanations method. …”
Get full text

A validated heart-specific model for splice-disrupting variants in childhood heart disease by Robert Lesurf, Jeroen Breckpot, Jade Bouwmeester, Nour Hanafi, Anjali Jain, Yijing Liang, Tanya Papaz, Jane Lougheed, Tapas Mondal, Mahmoud Alsalehi, Luis Altamirano-Diaz, Erwin Oechslin, Enrique Audain, Gregor Dombrowsky, Alex V. Postma, Odilia I. Woudstra, Berto J. Bouma, Marc-Phillip Hitz, Connie R. Bezzina, Gillian M. Blue, David S. Winlaw, Seema Mital

“…Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. …”
Get full text

A Hierarchical Machine Learning-Based Strategy for Mapping Grassland in Manitoba’s Diverse Ecoregions by Mirmajid Mousavi, James Kobina Mensah Biney, Barbara Kishchuk, Ali Youssef, Marcos R. C. Cordeiro, Glenn Friesen, Douglas Cattani, Mustapha Namous, Nasem Badreldin

“…This study developed a novel pixel-based grassland classification approach using three supervised machine learning (ML) algorithms, which were assessed in the province of Manitoba, Canada. …”
Get full text

Identification of sepsis biomarkers through glutamine metabolism-mediated immune regulation: a comprehensive analysis employing mendelian randomization, multi-omics integration, an... by Zhuang’e Shi, Fuping Wang, Lishun Yang, Lishun Yang, Couwen Li, Bing Gong, Ruanxian Dai, Guobing Chen

“…The predictive models were constructed using the CatBoost, XGBoost, and NGBoost algorithms based on the data from GSE236713 and GSE28750. …”
Get full text

Results of a non-interventional multicenter observational study on the diagnosis and treatment of patients with axial psoriatic arthritis in rea-world clinical practice in the Russ... by T. V. Korotaeva, E. E. Gubar, E. Yu. Loginova, Yu. L. Korsakova, E. A. Vasilenko, I.-D. Yu. Ilyevsky, L. V. Ivanova, E. Yu. Akulinushkina, P. А. Shesternya, O. V. Matveychuk, Yu. Yu. Grabovetskaya, A. A. Barakat, M. A. Korolev, E. V. Zonova, O. A. Georginova, I. V. Kolotilina, I. M. Marusenko, I. B. Vinogradova, O. B. Nesmeyanova, N. E. Grigoriadi, A. V. Petrov, D. G. Krechikova, T. V. Kropotina, S. P. Yakupova, V. I. Mazurov

“…Switching therapy to bDMARDs led to a significant reduction in disease activity.In order to improve the quality of medical care, the Russian clinical guidelines for the treatment of patients with PsA and the algorithms for the diagnosis of axial involvement need to be comprehensively implemented.…”
Get full text

Brachial Plexopathy in Head and Neck Cancer Potentially Related to LET-Dependent RBE by Abanob Hanna, Anthony Casper, Roi Dagan, Hardev S. Grewal, Jiyeon Park, Eric D. Brooks, Erik Traneus, Lars Glimelius, Perry B. Johnson, Mohammad Saki, Yawei Zhang, Twyla R. Willoughby, Julie A. Bradley, Jackson Browne, Mark E. Artz

“…Conservative treatment with pentoxifylline, gabapentin, and physical therapy improved his symptoms. (2) Methods: The original treatment plan was retrospectively analyzed using Monte Carlo dose algorithms and LET-dependent RBE models from McMahon and McNamara. …”
Get full text

Beyond identification of familial hypercholesterolemia: Improving downstream visits and treatments in a large health care system by Harin Lee, Tarun Kadaru, Ruth Schneider, Taylor Triana, Carol Tujardon, Colby Ayers, Mujeeb Basit, Zahid Ahmad, Amit Khera

“…Several electronic health record (EHR) algorithms have been developed to improve identification of patients with FH. …”
Get full text

Cancer incidence in young adults aged 20 to 44 years old in the Siberian Federal District by L. D. Zhuikova, E. L. Choynzonov, A. D. Kaprin, A. O. Shakhzadova, O. A. Ananina, G. A. Kononova, L. V. Pikalova, M. Yu. Grishchenko, E. V. Denisov

“…The results of the study update the development of new organizational and clinical algorithms for medical observation of young men and women for the purpose of prevention or early diagnosis of tumor pathology, including for creating the feasibility of performing organpreserving treatment while preserving the reproductive potential of young patients.…”
Get full text

Calibración de cámaras de tiempo de vuelo: Ajuste adaptativo del tiempo de integración y análisis de la frecuencia de modulación by P. Gil, T. Kisler, G.J. García, C.A. Jara, J.A. Corrales

“…This method has been successfully tested on visual servoing algorithms with architecture âeye-in-handâ in which the sensory system consists of a ToF camera, in addition this methodology can be applied to other workspaces and scenarios. …”
Get full text

Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model by Jiaqi Zhang, Jianing Zhang, Zhihao Liu, Yudong Zhou, Xiaoni Zhao, Yalong Wang, Danni Li, Jinsui Du, Chenglong Duan, Yi Pan, Qi Tian, Feiqian Wang, Ke Wang, Lizhe Zhu, Bin Wang

“…Abstract Background As the most prevalent female malignancy worldwide, breast cancer frequently involves axillary lymph node metastasis (ALNM), which critically affects therapeutic algorithms. Current guidelines mandate preoperative ultrasound-guided axillary biopsy for suspicious lymph nodes, potentially exposing some low-risk patients with negative results to invasive risks. …”
Get full text

Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP by Bingkui Ren, Yuping Zhang, Siying Chen, Jinglong Dai, Junci Chong, Yifei Zhong, Mengkai Deng, Shaobo Jiang, Zhigang Chang

“…Model performance was compared​ to four other machine learning algorithms using the area under the curve (AUC). ​SHAP was utilized to interpret the XGBoost model. …”
Get full text

Can Stereoscopic Density Replace Planar Density for Forest Aboveground Biomass Estimation? A Case Study Using Airborne LiDAR and Landsat Data in Daxing’anling, China by Xuan Mu, Dan Zhao, Zhaoju Zheng, Cong Xu, Jinchen Wu, Ping Zhao, Xiaomin Li, Yong Pang, Yujin Zhao, Tianyu An, Yuan Zeng, Bingfang Wu

“…At the regional scale, high-precision AGB estimates derived from airborne LiDAR were combined with vegetation indices from the Landsat Thematic Mapper (TM), and topographic factors from DEM to develop regional-scale AGB estimation models, using SLR and random forest (RF) algorithms. The results of 10-fold cross-validation demonstrated the superiority of the stereo method over the planar method, with RF outperforming SLR. …”
Get full text

A photogrammetric approach to the estimation of distance to animals in camera trap images by B. Mirka, C.D. Lippitt, G.M. Harris, R. Converse, M. Gurule, S.E. Sesnie, M.J. Butler, D.R. Stewart, Z. Rossman

“…These methods have the potential, when paired with deep learning algorithms or crowdsourcing, to automate the process of wildlife identification and distance estimation, reducing the need for manual fieldwork or analysis while increasing the precision and replicability of population estimates. …”
Get full text

On the construction of a large-scale database of AI-assisted annotating lung ventilation-perfusion scintigraphy for pulmonary embolism (VQ4PEDB) by Amir Jabbarpour, Eric Moulton, Eric Moulton, Sanaz Kaviani, Sanaz Kaviani, Siraj Ghassel, Wanzhen Zeng, Wanzhen Zeng, Ramin Akbarian, Ramin Akbarian, Anne Couture, Aubert Roy, Richard Liu, Yousif A. Lucinian, Nuha Hejji, Nuha Hejji, Sukainah AlSulaiman, Sukainah AlSulaiman, Farnaz Shirazi, Farnaz Shirazi, Eugene Leung, Eugene Leung, Sierra Bonsall, Samir Arfin, Bruce G. Gray, Ran Klein, Ran Klein, Ran Klein, Ran Klein

“…Quality assurance involved manual inspections and algorithmic validation.ResultsA query of The Ottawa Hospital's data warehouse followed by initial data screening yielded 2,137 V/Q studies with 2,238 successfully retrieved as DICOM studies. …”
Get full text

GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women by Li Yi, Jaime E. Hart, Grete Wilt, Cindy R. Hu, Marcia Pescador Jimenez, Pi-I Debby Lin, Esra Suel, Perry Hystad, Steve Hankey, Wenwen Zhang, Jorge E. Chavarro, Francine Laden, Peter James

“…Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. …”
Get full text

Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy by Xuemei Li, Xuemei Li, Xuemei Li, Xuemei Li, Xuemei Li, Chao Xiong, Chao Xiong, Chao Xiong, Chao Xiong, Chao Xiong, Siyi Wang, Siyi Wang, Siyi Wang, Zhangjun Ren, Zhangjun Ren, Zhangjun Ren, Qi Jin, Qi Jin, Qi Jin, Jinhai Yu, Jinhai Yu, Jinhai Yu, Jinhai Yu, Jinhai Yu, Yunxiu Chen, Yunxiu Chen, Yunxiu Chen, Puying Gan, Puying Gan, Puying Gan, Puying Gan, Qihua Xu, Qihua Xu, Qihua Xu, Qihua Xu, Qihua Xu, Yaohua Wang, Yaohua Wang, Yaohua Wang, Yaohua Wang, Yaohua Wang, Hongfei Liao, Hongfei Liao, Hongfei Liao, Hongfei Liao, Hongfei Liao

“…The intersection of DEGs, hub genes and ferroptosis-related gene yielded key genes of ferroptosis. Machine learning algorithms identified OFGs of ferroptosis. Meanwhile, by comparing the expression of FRGs in the orbital adipose tissue and the orbital fibroblasts (OFs) of healthy controls and TAO patients, as well as co-culturing macrophages and OFs in vitro, the influence of macrophages on FRGs in OFs was explored. …”
Get full text

Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data by Renjie Lu, Shiyun Wang, Pinghua Chen, Fangfang Li, Fangfang Li, Pan Li, Qian Chen, Xuefei Li, Fangyu Li, Suxia Guo, Jinlin Zhang, Jinlin Zhang, Dan Liu, Zhijun Hu

“…Four machine learning algorithms were utilized, with the optimal model undergoing hyperparameter optimization to evaluate the significance of predictive factors.ResultsA total of 1,092 CKD patients were included, with 231 (21.2%) diagnosed with sarcopenia. …”
Get full text

Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Regression and classification models were developed using gradient boosting, random forest, and CatBoost algorithms. Regression models predicted vault height as a continuous variable, while classification models categorized vault heights into binary and multi-class tasks. …”
Get full text

Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules by Zhi Li, Wenjing Zhang, Jinyi Huang, Ling Lu, Dongming Xie, Jinrong Zhang, Jiamin Liang, Yuepeng Sui, Linyuan Liu, Jianjun Zou, Ao Lin, Lei Yang, Fuman Qiu, Zhaoting Hu, Mei Wu, Yibin Deng, Xin Zhang, Jiachun Lu

“…Three widely applicable machine learning algorithms (Random Forests, Gradient Boosting Machine, and XGBoost) were used to screen the metrics, and then the corresponding predictive models were constructed using discriminative analysis, and the best performing model was selected as the target model. …”
Get full text

Genetic variants and molecular profiling of 46,XY gonadal dysgenesis using whole-exome sequencing by Ning Zhang, Ning Zhang, Ning Zhang, Shuoming You, Shuoming You, Jingjing Guo, Jingjing Guo, Xingyu Chang, Xingyu Chang, Junjun Qiu, Junjun Qiu, Keqin Hua, Keqin Hua

“…These variant sites are conserved among species and were predicted to be damaging according to functional algorithms and protein analyses. Additionally, 71.4% of the GATA4 amino acid changes in 46,XY GD were located in or close to the N-terminal zinc finger (N-ZF) domain. …”
Get full text