Automatic Feature Selection for Imbalanced Echocardiogram Data Using Event-Based Self-Similarity by Huang-Nan Huang, Hong-Min Chen, Wei-Wen Lin, Rita Wiryasaputra, Yung-Cheng Chen, Yu-Huei Wang, Chao-Tung Yang

“…<b>Conclusions:</b> Our findings highlight the potential of machine learning-driven echocardiogram analysis to enhance patient care by providing accurate, data-driven assessments.…”
Get full text

Impact of serum calcium levels on the occurrence of sepsis and prognosis in hospitalized patients with concomitant psoriasis: a retrospective study based on the MIMIC-IV database by Xiaolong Zheng, Qianjin Su, Yedi Wang, Xuefeng Geng

“…Additionally, three distinct trajectory patterns based on serum calcium levels were identified, with the low calcium trajectory group exhibiting a higher risk of sepsis (OR=2.400, 95% CI: 1.163-5.068, P&lt;0.001).ConclusionSerum calcium levels serve as a significant predictive factor for the occurrence and prognosis of sepsis in hospitalized patients with psoriasis. …”
Get full text

Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data by Bo Lu, Bo Lu, Qingyun Liu, Hao Liu, Tianxiang Long, Tianxiang Long

“…The analysis of nonlinear effects revealed distinct thresholds and patterns of influence that differ from other urban environments, with some variables exhibiting fluctuated or U-shaped effects. …”
Get full text

Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks by Magdalena Fafrowicz, Marcin Tutajewski, Igor Sieradzki, Jeremi K. Ochab, Jeremi K. Ochab, Anna Ceglarek-Sroka, Koryna Lewandowska, Tadeusz Marek, Barbara Sikora-Wachowicz, Igor T. Podolak, Paweł Oświęcimka, Paweł Oświęcimka, Paweł Oświęcimka

“…Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. …”
Get full text

Analysis of LULC Change Dynamics That Have Occurred in Tuscany (Italy) Since 2007 by Lorenzo Arcidiaco, Manuela Corongiu

Get full text

Analysis of Microbiome for AP and CRC Discrimination by Alessio Rotelli, Ali Salman, Leandro Di Gloria, Giulia Nannini, Elena Niccolai, Alessio Luschi, Amedeo Amedei, Ernesto Iadanza

“…This involves a deeper exploration and augmentation of the condensed data to uncover new insights and patterns that might not be readily apparent in the original, more complex form. …”
Get full text

A computational framework to characterize and compare the tonal repertoires of toothed whales by Maia Austin, Julie N. Oswald, Manali Rege‐Colt, Emma Gagne, Eric Angel Ramos, Joëlle De Weerdt, Nicola Ransome, Laura J. May‐Collado

“…The integration of hard and fuzzy unsupervised machine learning analyses provided a multifaceted characterization of whistle repertoires based on identified patterns and structures. …”
Get full text

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics by Guansheng Li, Xiaoxing Tian, Enyao Wei, Feng Zhang, Huang Liu

“…RT-qPCR analysis confirmed that the expression patterns of the biomarkers were consistent with the dataset findings, reinforcing the reliability and validity of the bioinformatic analyses. …”
Get full text

Optimizing CNN-Based Diagnosis of Knee Osteoarthritis: Enhancing Model Accuracy with CleanLab Relabeling by Thomures Momenpour, Arafat Abu Mallouh

Get full text

Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis by Dongxu Qin, Yongquan Zheng, Libo Wang, Zhenyi Lin, Yao Yao, Weidong Fei, Caihong Zheng

“…Single-cell analysis was conducted to investigate the expression patterns of these diagnostic genes across various cellular subpopulations. …”
Get full text

Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey by Wei Gong, Wei Gong, Wei Gong, Xiaoxiao Hu, Huimin Cui, Huimin Cui, Yuxin Zhao, Yuxin Zhao, Hong Lin, Hong Lin, Hong Lin, Peng Sun, Peng Sun, Jianjun Yang, Jianjun Yang

“…Subgroup analyses showed variated associations by age and sex, with psychological and geographic factors playing a larger role among those aged ≥80.ConclusionThis study demonstrated the feasibility and interpretability of using machine learning to model complex risk patterns of multimorbidity. …”
Get full text

Analysis of ferritinophagy-related genes associated with the prognosis and regulatory mechanisms in non-small cell lung cancer by Yuan Hao, Xin Wang, Zerong Ni, Yuhui Ma, Jing Wang, Wen Su

Get full text

Recent developments of artificial intelligence methods for sea ice concentration monitoring using high-resolution imaging datasets by Marzuraikah Mohd Stofa, Siti Raihanah Abdani, Asraf Mohamed Moubark, Muhammad Ammirrul Atiqi Mohd Zainuri, Ahmad Asrul Ibrahim, Nor Azwan Mohamed Kamari, Mohd Asyraf Zulkifley

“…Comprehensive discussions of the aforementioned topics, including the main findings and patterns, are provided to stimulate future research.…”
Get full text

Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model by Lufeng Chen, Qingquan Chen, Zhimin Huang, Ling Yao, Jiajing Zhuang, Haibin Lu, Yifu Zeng, Jimin Fan, Ailing Song, Yixiang Zhang

Get full text

Feature-Driven EnsembleX: An Advanced Ensemble Framework for Enhanced MRI Abdomen Image Classification Using Feature Refinement and Boosting Techniques by Snehal V. Laddha, Rohini S. Ochawar

Get full text

Integrative analysis of seed morphology, geographic origin, and genetic structure in Medicago with implications for breeding and conservation by Seunghyun Lim, Sunchung Park, Insuck Baek, Jacob Botkin, Jae Hee Jang, Seok Min Hong, Brian M. Irish, Moon S. Kim, Lyndel W. Meinhardt, Shaun J. Curtin, Ezekiel Ahn

“…Conclusions Our integrated analysis of phenotypic, genetic, and geographic data, coupled with a machine learning-based GWAS approach, provides valuable insights into the diverse patterns within Medicago spp. …”
Get full text

Exploring the predictive value of structural covariance networks for the diagnosis of schizophrenia by Clara S. Vetter, Clara S. Vetter, Clara S. Vetter, Annika Bender, Dominic B. Dwyer, Dominic B. Dwyer, Dominic B. Dwyer, Max Montembeault, Anne Ruef, Katharine Chisholm, Lana Kambeitz-Ilankovic, Linda A. Antonucci, Stephan Ruhrmann, Joseph Kambeitz, Marlene Rosen, Theresa Lichtenstein, Anita Riecher-Rössler, Rachel Upthegrove, Raimo K. R. Salokangas, Jarmo Hietala, Christos Pantelis, Christos Pantelis, Rebekka Lencer, Rebekka Lencer, Eva Meisenzahl, Stephen J. Wood, Stephen J. Wood, Paolo Brambilla, Paolo Brambilla, Stefan Borgwardt, Peter Falkai, Peter Falkai, Alessandro Bertolino, Nikolaos Koutsouleris, Nikolaos Koutsouleris, Nikolaos Koutsouleris, PRONIA Consortium

“…Risk estimates derived from KLS-SCNs and regional GMV, but not REF-SCNs, could be predicted from clinical variables, especially driven by body mass index (BMI) and affect-related negative symptoms.DiscussionThese patterns of results show that different SCN computation approaches capture different aspects of the disease. …”
Get full text

Prediction of Key Quality Parameters in Hot Air-Dried Jujubes Based on Hyperspectral Imaging by Quancheng Liu, Chunzhan Yu, Yuxuan Ma, Hongwei Zhang, Lei Yan, Shuxiang Fan

Get full text

Comprehensive Analysis of Programmed Cell Death-Related Genes in Diagnosis and Synovitis During Osteoarthritis Development: Based on Bulk and Single-Cell RNA Sequencing Data by Zhou J, Jiao S, Huang J, Dai T, Xu Y, Xia D, Feng Z, Chen J, Li Z, Hu L, Meng Q

“…The five screened Hub PCD-DEGs (TNFAIP3, JUN, PPP1R15A, INHBB and DDIT4) could be explored as candidate biomarkers or therapeutic targets for OA.Keywords: osteoarthritis, programmed cell death, bioinformatics, machine learning, immune infiltration, biomarkers…”
Get full text

A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Advanced predictive models like logistic Regression and XGBoost analyze critical variables, identify patterns, and perform predictive analysis. These models can identify potential impactions, assess impaction type, and develop treatment plans. …”
Get full text