Artificial Intelligence and Digital Medicine

29 Items

All Items

Screening and validating genes associated with cuproptosis in systemic lupus erythematosus by expression profiling combined with machine learning

Zhongbin Xia, Ruoying Cheng, Qi Liu, Yuxin Zu, Shilu Liao

965–975
Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005–2020

Haoxun Zhang, Guoling Zhang, Chunyang Wang

2229–2242
OncoImmune machine-learning model predicts immune response and prognosis in leiomyosarcoma

Jingrong Deng, Changfa Shu, Dong Wang, Richard Nimbona, Xingping Zhao, Dabao Xu

2308–2323
NEWS, SIRS and qSOFA criteria for predicting sepsis and sepsis with high risk of death in emergency room: A comparison study and improved predictive models based on local data from CETAT and MIMIC-IV databases

Wenwen Wang, Kaipeng Wang, Yueguo Wang, Qingyuan Liu, Jian Sun, Ronghua Shi, Sicheng Liu, Huanli Wang, Yuan Yuan, Jun Xu, Kui Jin, Yixin Zhang

1470–1478
Machine learning to improve prognosis prediction of metastatic clear-cell renal cell carcinoma treated with cytoreductive nephrectomy and systemic therapy

Wenjie Yang, Lin Ma, Jie Dong, Mengchao Wei, Ruoyu Ji, Hualin Chen, Xiaoqiang Xue, Yingjie Li, Zhaoheng Jin, Weifeng Xu, Zhigang Ji

471–482
Machine learning integration of single-cell and bulk transcriptomics identifies fibroblast-driven prognostic markers in colorectal cancer

Ning Zhang, Ruiyan Liu, Siya Wu, Chenxi Feng, Boxiang Wang, Qiaoqiao Zheng, Linru Jie, Ruihua Kang, Xiaoli Guo, Xiaoyang Wang, Shaokai Zhang, Jiangong Zhang

115–131
Machine learning for predicting the survival in osteosarcoma patients: Analysis based on American and Hebei Province cohort

Yahui Hao, Di Liang, Shuo Zhang, Siqi Wu, Daojuan Li, Yingying Wang, Miaomiao Shi, Yutong He

883–893
Leveraging artificial intelligence to identify high-risk patients for postoperative sore throat: An observational study

Qiangqiang Zhou, Xiaoya Liu, Huifang Yun, Yahong Zhao, Kun Shu, Yong Chen, Song Chen

593–605
Gaining consensus on expert rule statements for acute respiratory failure digital twin patient model in intensive care unit using a Delphi method

Amy J. Montgomery, John Litell, Johnny Dang, Laure Flurin, Ognjen Gajic, Amos Lal, on behalf of Digital Twin Platform for education, research, and healthcare delivery investigator group

1108–1117
Enhancing predictions of health insurance overspending risk through hospital departmental performance indicators

Yao Bu, Danqi Wang, Xiaomao Fan, Jiongying Li, Lei Hua, Lin Zhang, Wenjun Ma, Liwen He, Hao Zang, Haijun Zhang, Xingyu Liu, Yufeng Gao, Li Liu

2269–2280
$Enhancing clinical decision-making in closed pelvic fractures with machine learning models$

Enhancing clinical decision-making in closed pelvic fractures with machine learning models

Dian Wang, Yongxin Li, Li Wang

1491–1507
Early machine learning prediction of hospitalized patients at low risk of respiratory deterioration or mortality in community-acquired pneumonia: Derivation and validation of a multivariable model

Yewande E. Odeyemi, Amos Lal, Erin F. Barreto, Allison M. LeMahieu, Hemang Yadav, Ognjen Gajic, Phillip Schulte

337–345
E-DFu-Net: An efficient deep convolutional neural network models for Diabetic Foot Ulcer classification

Nouf F. Almufadi, Haifa F. Alhasson, Shuaa S. Alharbi

445–460
Development of a novel clinical prediction model for sepsis related mortality by combining NEWS, PIRO and lactate

Ozge Kurtkulagi, Ece Unal Cetin, Fatih Kamis, Murat Das, Esen Simsek, Ozgur Kurtkulagi, Adil Ugur Cetin, Yavuz Beyazit

2570–2577
Development and validation of radiomics machine learning model based on contrast-enhanced computed tomography to predict axillary lymph node metastasis in breast cancer

Jieqiu Zhang, Gaofei Cao, Haowen Pang, Jin Li, Xiaopeng Yao

317–326
Development and validation of a preliminary multivariable diagnostic model for identifying unusual infections in hospitalized patients

Aysun Tekin, Mohammad Joghataee, Lucrezia Rovati, Hong Truong, Claudia Castillo-Zambrano, Kushagra Kushagra, Nasrin Nikravangolsefid, Mahmut Ozkan, Ashish Gupta, Vitaly Herasevich, Juan Domecq, John O’Horo, Ognjen Gajic

1387–1399
Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms

Chengqian Huang, Jing Zhuo, Chong Liu, Shaofeng Wu, Jichong Zhu, Tianyou Chen, Bin Zhang, Sitan Feng, Chenxing Zhou, Zequn Wang, Shengsheng Huang, Liyi Chen, Xinli Zhan

401–410
Development and evaluation of interpretable machine learning regressors for predicting femoral neck bone mineral density in elderly men using NHANES data

Wen He, Song Chen, Xianghong Fu, Licong Xu, Jun Xie, Jinxing Wan

375–390
Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI

Yuhong Fan, Kaixiang Sun, Yao Xiao, Peng Zhong, Yun Meng, Yang Yang, Zhenwei Du, Jingqin Fang

2243–2251
$Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection$

Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection

Qingming Ye, Zhilu Wang, Yi Lou, Yang Yang, Jue Hou, Zheng Liu, Weiguang Liu, Jiayu Li

1631–1646

1-20 of 29 Next

Artificial Intelligence and Digital Medicine

All Items

Screening and validating genes associated with cuproptosis in systemic lupus erythematosus by expression profiling combined with machine learning

Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005–2020

OncoImmune machine-learning model predicts immune response and prognosis in leiomyosarcoma

NEWS, SIRS and qSOFA criteria for predicting sepsis and sepsis with high risk of death in emergency room: A comparison study and improved predictive models based on local data from CETAT and MIMIC-IV databases

Machine learning to improve prognosis prediction of metastatic clear-cell renal cell carcinoma treated with cytoreductive nephrectomy and systemic therapy

Machine learning integration of single-cell and bulk transcriptomics identifies fibroblast-driven prognostic markers in colorectal cancer

Machine learning for predicting the survival in osteosarcoma patients: Analysis based on American and Hebei Province cohort

Leveraging artificial intelligence to identify high-risk patients for postoperative sore throat: An observational study

Gaining consensus on expert rule statements for acute respiratory failure digital twin patient model in intensive care unit using a Delphi method

Enhancing predictions of health insurance overspending risk through hospital departmental performance indicators

Enhancing clinical decision-making in closed pelvic fractures with machine learning models

Early machine learning prediction of hospitalized patients at low risk of respiratory deterioration or mortality in community-acquired pneumonia: Derivation and validation of a multivariable model

E-DFu-Net: An efficient deep convolutional neural network models for Diabetic Foot Ulcer classification

Development of a novel clinical prediction model for sepsis related mortality by combining NEWS, PIRO and lactate

Development and validation of radiomics machine learning model based on contrast-enhanced computed tomography to predict axillary lymph node metastasis in breast cancer

Development and validation of a preliminary multivariable diagnostic model for identifying unusual infections in hospitalized patients

Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms

Development and evaluation of interpretable machine learning regressors for predicting femoral neck bone mineral density in elderly men using NHANES data

Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI

Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection

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