Results 221 to 230 of about 2,651,054 (356)

Cross-sectional study of health impairment related to post COVID-19 condition among participants of a large population-based cohort in Germany. [PDF]

Sci Rep
Diexer S, Frost J, Ahnert P, Baernighausen TW, Brenner H, Fricke J, Gabrysch S, Greiser KH, Harth V, Heise JK, Kaaks R, Karch A, Keil T, Klee B, Klett-Tammen CJ, Krist L, Lampl BMJ, Leitzmann MF, Lieb W, Meinke-Franze C, Michels KB, Velásquez IM, Obi N, Peters A, Pfrommer LR, Pischon T, Purschke O, Rübsamen N, Schikowski T, Schmidt B, Thierry S, Völzke H, Wright MN, Zeeb H, Mikolajczyk R.   +34 more
europepmc   +1 more source

EPIDEMIC POLIOMYELITIS: EPIDEMIOLOGY, CAUSES, AND PREVENTION [PDF]

, 1936
A. S. MacNalty
openalex   +1 more source

Artificial Intelligence‐Assisted Urine Cytology for Noninvasive Detection of Muscle‐Invasive Urothelial Carcinoma: A Multi‐Center Diagnostic Study with Prospective Validation

Advanced Science, EarlyView.
Accurate preoperative detection of muscle‐invasive urothelial carcinoma (MIUC) is crucial for clinical decision‐making. This study developed PUCAS‐M, an artificial intelligence (AI) model that analyzes urine cytology to assist in differentiating MIUC from non‐MIUC.
Runnan Shen, Fan Jiang, Xiaowei Huang, Guibin Hong, Yun Luo, Huan Wan, Ye Xie, Mengyi Zhu, Yun Wang, Bohao Liu, Ping Qin, Yahui Wang, Haoxuan Wang, Hongkun Yang, Zhen Lin, Rui Chen, Nengtai Ouyang, Jian Huang, Tianxin Lin, Shaoxu Wu   +19 more
wiley   +1 more source

Comparisons of Nutri-Score and NutrInform Battery on consumer preferences, objective understanding, and food choices among Portuguese consumers. [PDF]

Eur J Public Health
Vasseur T, Fialon M, Marques-Vidal P, Pereira P, Meirhaeghe A, Galan P, Kesse-Guyot E, Touvier M, Deschasaux-Tanguy M, Sarda B, Hercberg S, Nabec L, Julia C.   +12 more
europepmc   +1 more source

Artificial Intelligence‐Driven Proteomics Identifies Plasma Protein Signatures for Diagnosis and Stratification of Behçet's Disease

Advanced Science, EarlyView.
Molecular and functional landscape of BD progression and severity based on in‐depth proteomics. Tree boosting machine learning models with favorable performance in BD diagnosis and stratification. Efficient biomarker panels for BD diagnosis and stratification. .
Linlin Cheng, Mansheng Li, Zhou Bai, Xiaobo Yu, Wenjie Zheng, Yongzhe Li, Yudong Liu   +6 more
wiley   +1 more source

Uncertainty in epidemiology and health risk assessment [PDF]

, 2009
D J, Briggs, K, Lee, Sabel, Clive E
core   +1 more source

Clinical Epidemiology [PDF]

, 1948
W. S. C. Copeman
openalex   +1 more source

GLM7 – A Novel Composite Glycolipid Index Derived from Routine Health Indicators for Enhanced Diagnosis and Prediction of Multimorbidity

Advanced Science, EarlyView.
This study leverages NHANES data to analyze 49 routine indicators, identifying the top 10 diagnostic markers for five major diseases and introducing GLM7, a novel indicator. Restricted cubic spline analyses, forest plot evaluations, and XGBoost modeling demonstrate conventional indicators' efficacy and GLM7's value for disease diagnosis/prediction ...
Zhihua Wang, Shuo Chen, Xiaojun Feng, Xi Chen, Paul C Evans, Hans Strijdom, Yu Ding, Jianping Weng, Suowen Xu   +8 more
wiley   +1 more source

Experimental Epidemiology

Science, 1932
openaire   +3 more sources

First Principles: And Epidemiology.

, 1920
F. G. Crookshank
openalex   +1 more source