Filter

Refine by collections

Refine by date

—
  • Print
  • Save

Search Results

You are looking at 1 - 10 of 35 items for :

  • "predictive model" x
Clear All
Rongpeng Gong Medical College of Qinghai University, Xining, People’s Republic of China

Search for other papers by Rongpeng Gong in
Google Scholar
PubMed Close
,
Yuanyuan Liu Medical College of Qinghai University, Xining, People’s Republic of China

Search for other papers by Yuanyuan Liu in
Google Scholar
PubMed Close
,
Gang Luo Medical College of Qinghai University, Xining, People’s Republic of China

Search for other papers by Gang Luo in
Google Scholar
PubMed Close
,
Jiahui Yin College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China

Search for other papers by Jiahui Yin in
Google Scholar
PubMed Close
,
Zuomiao Xiao Department of Clinical Laboratory, The Affiliated Ganzhou Hospital of Nanchang University, Ganzhou, China

Search for other papers by Zuomiao Xiao in
Google Scholar
PubMed Close
, and
Tianyang Hu Precision Medicine Center, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China

Search for other papers by Tianyang Hu in
Google Scholar
PubMed Close

identify subjects with IR early. At present, several predictive models for IR have been established. For example, in 2018, Boursier et al. used triglycerides and glycated hemoglobin to predict IR in an obese population ( 15 ). Yeh et al. proposed a

Article Type:
Research Article
Collections:
Metabolic Syndrome and Diabetes
DOI:
https://doi.org/10.1530/EC-22-0066
Volume/Issue:
Volume 11: Issue 7
Open access
Lei Gao Department of Geriatrics, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China

Search for other papers by Lei Gao in
Google Scholar
PubMed Close
,
Wenxia Cui Department of Geriatrics, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China

Search for other papers by Wenxia Cui in
Google Scholar
PubMed Close
,
Dinghuang Mu Department of Geriatrics, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China

Search for other papers by Dinghuang Mu in
Google Scholar
PubMed Close
,
Shaoping Li Department of Health Management Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China

Search for other papers by Shaoping Li in
Google Scholar
PubMed Close
,
Nan Li Department of Geriatrics, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China

Search for other papers by Nan Li in
Google Scholar
PubMed Close
,
Weihong Zhou Department of Health Management Center, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China

Search for other papers by Weihong Zhou in
Google Scholar
PubMed Close
, and
Yun Hu Department of Geriatrics, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China

Search for other papers by Yun Hu in
Google Scholar
PubMed Close

, alanine aminotransferase; UA, uric acid; TG, triglycerides; HDL, high-density lipoprotein. Internal validation of predictive model Figure 4 illustrates the ROC curves for the nomogram. The AUC of the training set is 0.795 (95% CI: 0

Article Type:
Research Article
Collections:
Obesity
DOI:
https://doi.org/10.1530/EC-24-0186
Volume/Issue:
Volume 13: Issue 8
Open access
Lian Duan Department of Nuclear Medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Lian Duan in
Google Scholar
PubMed Close
,
Han-Yu Zhang Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Han-Yu Zhang in
Google Scholar
PubMed Close
,
Min Lv Department of Nuclear Medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Min Lv in
Google Scholar
PubMed Close
,
Han Zhang Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Han Zhang in
Google Scholar
PubMed Close
,
Yao Chen Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Yao Chen in
Google Scholar
PubMed Close
,
Ting Wang Department of Nuclear Medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Ting Wang in
Google Scholar
PubMed Close
,
Yan Li Department of Nuclear Medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Yan Li in
Google Scholar
PubMed Close
,
Yan Wu Department of Clinical Laboratory, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China

Search for other papers by Yan Wu in
Google Scholar
PubMed Close
,
Junfeng Li Department of Radiology, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

Search for other papers by Junfeng Li in
Google Scholar
PubMed Close
, and
Kefeng Li School of Medicine, University of California, San Diego, California, USA

Search for other papers by Kefeng Li in
Google Scholar
PubMed Close

dose after thyroidectomy, but prediction of early HT after RAI has not been reported ( 16 , 17 ). In this study, we developed a multi-feature predictive model based on the real-world EMR using the combination of multiple machine learning approaches

Article Type:
Research Article
Collections:
Thyroid
DOI:
https://doi.org/10.1530/EC-22-0119
Volume/Issue:
Volume 11: Issue 5
Open access
Hongyan Wang Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

Search for other papers by Hongyan Wang in
Google Scholar
PubMed Close
,
Bin Wu Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

Search for other papers by Bin Wu in
Google Scholar
PubMed Close
,
Zichuan Yao Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

Search for other papers by Zichuan Yao in
Google Scholar
PubMed Close
,
Xianqing Zhu Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

Search for other papers by Xianqing Zhu in
Google Scholar
PubMed Close
,
Yunzhong Jiang Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

Search for other papers by Yunzhong Jiang in
Google Scholar
PubMed Close
, and
Song Bai Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

Search for other papers by Song Bai in
Google Scholar
PubMed Close

). At present, risk factors related to surgery-associated morbidity remain unclear due to the limited number of studies about this issue and the inconsistency of the conclusions. A nomogram derived from predictive model is accepted as a reliable tool

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-20-0004
Volume/Issue:
Volume 9: Issue 4
Open access
Lu Yang Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

Search for other papers by Lu Yang in
Google Scholar
PubMed Close
,
Xingguo Jing Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

Search for other papers by Xingguo Jing in
Google Scholar
PubMed Close
,
Hua Pang Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

Search for other papers by Hua Pang in
Google Scholar
PubMed Close
,
Lili Guan Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

Search for other papers by Lili Guan in
Google Scholar
PubMed Close
, and
Mengdan Li Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

Search for other papers by Mengdan Li in
Google Scholar
PubMed Close

best results in MGD prediction. Looking forward, more integrated predictive models need to be explored to help clinicians develop optimal MGD treatment plans and reduce the incidence of postoperative PHPT persistence or recurrence. Meanwhile, the

Article Type:
Review Article
Collections:
Bone and Mineral Metabolism
DOI:
https://doi.org/10.1530/EC-23-0492
Volume/Issue:
Volume 13: Issue 5
Open access
Yaqian Mao Shengli Clinical Medical College of Fujian Medical University, Fujian, China
Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

Search for other papers by Yaqian Mao in
Google Scholar
PubMed Close
,
Lizhen Xu Shengli Clinical Medical College of Fujian Medical University, Fujian, China

Search for other papers by Lizhen Xu in
Google Scholar
PubMed Close
,
Ting Xue Shengli Clinical Medical College of Fujian Medical University, Fujian, China

Search for other papers by Ting Xue in
Google Scholar
PubMed Close
,
Jixing Liang Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

Search for other papers by Jixing Liang in
Google Scholar
PubMed Close
,
Wei Lin Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

Search for other papers by Wei Lin in
Google Scholar
PubMed Close
,
Junping Wen Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

Search for other papers by Junping Wen in
Google Scholar
PubMed Close
,
Huibin Huang Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

Search for other papers by Huibin Huang in
Google Scholar
PubMed Close
,
Liantao Li Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

Search for other papers by Liantao Li in
Google Scholar
PubMed Close
, and
Gang Chen Shengli Clinical Medical College of Fujian Medical University, Fujian, China
Department of Endocrinology, Fujian Provincial Hospital, Fujian, China
Fujian Provincial Key Laboratory of Medical Analysis, Fujian Academy of Medical, Fujian, China

Search for other papers by Gang Chen in
Google Scholar
PubMed Close

-square test, and the value of P < 0.05 (two-sided) was considered statistically significant. In the construction of the predictive model, we used the least absolute shrinkage and selection operator (LASSO) regression analysis to screen out characteristic

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0330
Volume/Issue:
Volume 10: Issue 9
Open access
Beibei Zhu School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Beibei Zhu in
Google Scholar
PubMed Close
,
Yan Han School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Yan Han in
Google Scholar
PubMed Close
,
Fen Deng School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Fen Deng in
Google Scholar
PubMed Close
,
Kun Huang School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Kun Huang in
Google Scholar
PubMed Close
,
Shuangqin Yan Ma’anshan Maternal and Child Health Care Center, Ma’anshan, Anhui, China

Search for other papers by Shuangqin Yan in
Google Scholar
PubMed Close
,
Jiahu Hao School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Jiahu Hao in
Google Scholar
PubMed Close
,
Peng Zhu School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Peng Zhu in
Google Scholar
PubMed Close
, and
Fangbiao Tao School of Public Health, Anhui Medical University, Hefei, Anhui, China
Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People’s Republic of China, Hefei, Anhui, China
NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Hefei, Anhui, China
Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, Anhui, China

Search for other papers by Fangbiao Tao in
Google Scholar
PubMed Close

vs both). To further specify the clinical significance of T3 and T3/fT4, we built multivariate predictive models along with routine variables (i.e. maternal age, pre-pregnancy BMI, history of family diabetes, gestational seasons, fasting plasma

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0088
Volume/Issue:
Volume 10: Issue 7
Open access
Yang Lv Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Yang Lv in
Google Scholar
PubMed Close
,
Ning Pu Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Ning Pu in
Google Scholar
PubMed Close
,
Wei-lin Mao Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Wei-lin Mao in
Google Scholar
PubMed Close
,
Wen-qi Chen Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Wen-qi Chen in
Google Scholar
PubMed Close
,
Huan-yu Wang Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Huan-yu Wang in
Google Scholar
PubMed Close
,
Xu Han Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Xu Han in
Google Scholar
PubMed Close
,
Yuan Ji Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Yuan Ji in
Google Scholar
PubMed Close
,
Lei Zhang Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Lei Zhang in
Google Scholar
PubMed Close
,
Da-yong Jin Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Da-yong Jin in
Google Scholar
PubMed Close
,
Wen-Hui Lou Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Wen-Hui Lou in
Google Scholar
PubMed Close
, and
Xue-feng Xu Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China

Search for other papers by Xue-feng Xu in
Google Scholar
PubMed Close

, nomograms based on both SEER data and our data were developed in this study to reveal good discrimination capability to predict different OS rates. In the future, the more advanced predictive model for this disease will be obtained to assist in risk

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-18-0353
Volume/Issue:
Volume 7: Issue 11
Open access
Yuegui Wang Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

Search for other papers by Yuegui Wang in
Google Scholar
PubMed Close
,
Liwei Hong Department of Nuclear Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

Search for other papers by Liwei Hong in
Google Scholar
PubMed Close
,
Caiyun Yang Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China

Search for other papers by Caiyun Yang in
Google Scholar
PubMed Close
,
Guorong Lv School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China
Quanzhou Medical College, Quanzhou, Fujian, China

Search for other papers by Guorong Lv in
Google Scholar
PubMed Close
,
Kangjian Wang Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

Search for other papers by Kangjian Wang in
Google Scholar
PubMed Close
,
Xuepeng Huang Department of Nuclear Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

Search for other papers by Xuepeng Huang in
Google Scholar
PubMed Close
, and
Haolin Shen Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

Search for other papers by Haolin Shen in
Google Scholar
PubMed Close

failure and can significantly impact patients with hypermetabolic syndrome. To enhance treatment success rates, evaluating factors associated with NHRH and establishing a predictive model are crucial. Previous studies explored factors such as age, sex

Article Type:
Research Article
Collections:
Thyroid
DOI:
https://doi.org/10.1530/EC-23-0429
Volume/Issue:
Volume 13: Issue 2
Open access
Kelly Brewer Center for Molecular Oncology, University of Connecticut School of Medicine, Farmington, Connecticut, USA

Search for other papers by Kelly Brewer in
Google Scholar
PubMed Close
,
Isabel Nip Center for Molecular Oncology, University of Connecticut School of Medicine, Farmington, Connecticut, USA

Search for other papers by Isabel Nip in
Google Scholar
PubMed Close
,
Justin Bellizzi Center for Molecular Oncology, University of Connecticut School of Medicine, Farmington, Connecticut, USA

Search for other papers by Justin Bellizzi in
Google Scholar
PubMed Close
,
Jessica Costa-Guda Center for Molecular Oncology, University of Connecticut School of Medicine, Farmington, Connecticut, USA
Center for Regenerative Medicine and Skeletal Development, Department of Reconstructive Sciences, University of Connecticut School of Dental Medicine, Farmington, Connecticut, USA

Search for other papers by Jessica Costa-Guda in
Google Scholar
PubMed Close
, and
Andrew Arnold Center for Molecular Oncology, University of Connecticut School of Medicine, Farmington, Connecticut, USA
Division of Endocrinology and Metabolism, University of Connecticut School of Medicine, Farmington, Connecticut, USA

Search for other papers by Andrew Arnold in
Google Scholar
PubMed Close

. Variant databases dbSNP ( 33 ), COSMIC ( 34 ), and ClinVar ( 35 ) were queried for any identified variants. Variants were assessed by predictive modeling tools SIFT ( 36 ) and Poly-Phen ( 37 ), and meta prediction tools REVEL ( 38 ) and MetaLR/dbNSFP ( 39

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0055
Volume/Issue:
Volume 10: Issue 3
Open access