Multi-Target Mechanism of Compound Qingdai Capsule for Treatment of Psoriasis: Multi-Omics Analysis and Experimental Verification by Qiao Y, Li C, Chen C, Wu P, Yang Y, Xie M, Liu N, Gu J

“…CQC ingredients-targets network was constructed using these ingredients and their targets. Screening of CQC anti-psoriasis core targets using machine learning algorithm. …”
Get full text

Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma by Zhen Chen, Yongjun Zhang

“…Considering the critical role of tumor infiltrating lymphocytes in effective immunotherapy, this study was designed to screen molecular markers related to tumor infiltrating cells in LUAD, aiming to improve immunotherapy response during LUAD therapy. …”
Get full text

Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation by Sixuan Wu, Yuanbin Tang, Qihong Pan, Yaqin Zheng, Yeru Tan, Junfan Pan, Yuehua Li

“…In addition, a machine learning model constructed based on Stepglm[backward] with the random forest algorithm achieved the highest C-index (0.999) and screened eight core genes, among which ST14 was noted for its excellent predictive ability. …”
Get full text

Exhaled volatile organic compounds as novel biomarkers for early detection of COPD, asthma, and PRISm: a cross-sectional study by Jiaxin Tian, Qiurui Zhang, Minhua Peng, Leixin Guo, Qianqian Zhao, Wei Lin, Sitong Chen, Xuefei Liu, Simin Xie, Wenxin Wu, Yijie Li, Junqi Wang, Jin Cao, Ping Wang, Min Zhou

“…Subsequently, classification models were established by machine learning algorithms, based on these VOC markers along with baseline characteristics. …”
Get full text

High-flow nasal cannula therapy versus continuous positive airway pressure for non-invasive respiratory support in paediatric critical care: the FIRST-ABC RCTs by Padmanabhan Ramnarayan, Alvin Richards-Belle, Karen Thomas, Laura Drikite, Zia Sadique, Silvia Moler Zapata, Robert Darnell, Carly Au, Peter J Davis, Izabella Orzechowska, Julie Lester, Kevin Morris, Millie Parke, Mark Peters, Sam Peters, Michelle Saull, Lyvonne Tume, Richard G Feltbower, Richard Grieve, Paul R Mouncey, David Harrison, Kathryn Rowan

“…More patients switched from CPAP to HFNC (30.9%) than from HFNC to CPAP (20.0%). …”
Get full text

Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis by Yanan Li, Yuqiu Tan, Zengwen Ma, Zengwen Ma, Weiwei Qian, Weiwei Qian

“…Further combining cell death-related gene screening and four machine learning algorithms (including LASSO-logistic, Gradient Boosting Machine, Random Forest and xGBoost), nine SeALAR-characterized cell death genes (SeDGs) were screened and a risk prediction model based on SeDGs was constructed that demonstrated good prediction performance. …”
Get full text

Opening closed doors: using machine learning to explore factors associated with marital sexual violence in a cross-sectional study from India by Anita Raj, Abhishek Singh, Nandita Bhan, Lotus McDougal, Nabamallika Dehingia, Julian McAuley

“…Analyses included iterative thematic analysis (L-1 regularised regression followed by iterative qualitative thematic coding of L-2 regularised regression results) and neural network modelling.Outcome measure Participants reported their experiences of sexual violence perpetrated by their current (or most recent) husband in the previous 12 months. …”
Get full text

Improving the accuracy of remotely sensed TSS and turbidity using quality enhanced water reflectance by a statistical resampling technique by Kunwar Abhishek Singh, Dongryeol Ryu, Meenakshi Arora, Manoj Kumar Tiwari, Bhabagrahi Sahoo

“…The statistical resampling approach based on GMM was applied to Sentinel-2 (S2) imagery to produce input to Machine Learning (ML) algorithms to retrieve the TSS and turbidity for target river sections. …”
Get full text

Characterization and stratification of risk factors of stroke in people living with HIV: A theory-informed systematic review by Martins Nweke, Nombeko Mshunqane

“…Predictive and preventative models should target factors with a high causality index and low investigative costs. …”
Get full text

A Deep Learning Method for Pneumoconiosis Staging on Chest X-Ray Under Label Noise by Wenjian Sun, Dongsheng Wu, Jiang Shen, Yang Luo, Hao Wang, Li Min, Chunbo Luo

“…The ambiguous properties of small opacities in pneumoconiosis chest radiographs can cause diagnostic drift, which in turn leads to the presence of noisy labels in the datasets collected from hospitals that can negatively impact the generalization of deep learning models. To tackle this issue, we propose COFINE, a novel coarse-to-fine noise-tolerant deep learning method for the staging of pneumoconiosis chest radiographs, which comprises two procedures: coarse screening and fine learning. …”
Get full text

Mechanical positioning of multiple nuclei in muscle cells. by Angelika Manhart, Stefanie Windner, Mary Baylies, Alex Mogilner

Get full text

Spatial and temporal distribution patterns and factors influencing hepatitis B in China: a geo-epidemiological study by Kang Fang, Na Cheng, Chuang Nie, Wentao Song, Yunkang Zhao, Jie Pan, Qi Yin, Jiwei Zheng, Qinglin Chen, Tianxin Xiang

“…Spatial autocorrelation analysis and spatiotemporal scanning were used to analyze the spatiotemporal distribution characteristics. The random forest algorithm was used to screen the potential influencing factors. …”
Get full text

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders by Ziqin Yang, Ziqin Yang, Nicole A. Teaney, Nicole A. Teaney, Elizabeth D. Buttermore, Elizabeth D. Buttermore, Elizabeth D. Buttermore, Mustafa Sahin, Mustafa Sahin, Mustafa Sahin, Wardiya Afshar-Saber, Wardiya Afshar-Saber

“…In this review, we compare two-dimensional and three-dimensional hiPSC formats for disease modeling, discuss the applications of functional assays, and offer insights on incorporating ML into hiPSC-based NDD research and drug screening.…”
Get full text

Identification and verification of XDH genes in ROS induced oxidative stress response of osteoarthritis based on bioinformatics analysis by Chengze Qiu, Zhiyong Zhang, Haocheng Wang, Na Liu, Ruixin Li, Zhiheng Wei, Benjie Wang, Nan Zhang

“…An artificial neural network model was constructed for the hub genes, and immune analysis was conducted using the ssGSEA algorithm. …”
Get full text

Uso de inteligencia artificial para predecir complicaciones en cirugías de columna toracolumbar degenerativa: revisión sistemática by G. Ricciardi, J.I. Cirillo Totera, R. Pons Belmonte, L. Romero Valverde, F. López Muñoz, A. Manríquez Díaz

“…Due to heterogeneity in samples, outcomes of interest, and algorithm evaluation metrics, a meta-analysis was not performed. …”
Get full text

[Translated article] Use of artificial intelligence to predict complications in degenerative thoracolumbar spine surgery: A systematic review by G. Ricciardi, J.I. Cirillo Totera, R. Pons Belmonte, L. Romero Valverde, F. López Muñoz, A. Manríquez Díaz

“…In 5 (41.6%) articles, the effectiveness of artificial intelligence predictive models was compared with conventional techniques. …”
Get full text

Exploring pesticide risk in autism via integrative machine learning and network toxicology by Ling Qi, Jingran Yang, Qiao Niu, Jianan Li

“…Each combination of 1–23 targets was used to construct predictive models using eight different machine learning algorithms. …”
Get full text

Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target by Guangyang Cheng, Zhaokai Zhou, Shiqi Li, Fu Peng, Shuai Yang, Chuanchuan Ren

“…Finally, a novel RCC prognostic marker PIF1 was identified in model genes. The knockdown of PIF1 in vitro inhibited the progression of renal carcinoma cells. …”
Get full text

Identification and validation of the diagnostic biomarker MFAP5 for CAVD with type 2 diabetes by bioinformatics analysis by Qiang Shen, Lin Fan, Chen Jiang, Dingyi Yao, Xingyu Qian, Fuqiang Tong, Zhengfeng Fan, Zongtao Liu, Nianguo Dong, Chao Zhang, Jiawei Shi

“…Machine learning (ML) algorithms were employed to screen potential biomarkers. …”
Get full text

Signatures of Six Autophagy‐Related Genes as Diagnostic Markers of Thyroid‐Associated Ophthalmopathy and Their Correlation With Immune Infiltration by Qintao Ma, Yuanping Hai, Jie Shen

“…The combined six‐gene model also showed good diagnostic efficacy (AUC = 0.948). …”
Get full text