Concerns regarding “Development of a machine learning-based model to predict hepatic inflammation in chronic hepatitis B patients with concurrent hepatic steatosis …
Z Geng, T Guo, L Wei, K Wang - EClinicalMedicine, 2024 - thelancet.com
I recently read the article published in your journal, titled “Development of a machine
learning-based model to predict hepatic inflammation in chronic hepatitis B patients with …
learning-based model to predict hepatic inflammation in chronic hepatitis B patients with …
A predictive model for disease severity among COVID-19 elderly patients based on IgG subtypes and machine learning
Z Zhuang, Y Qi, Y Yao, Y Yu - Frontiers in Immunology, 2023 - frontiersin.org
Objective Due to the increased likelihood of progression of severe pneumonia, the mortality
rate of the elderly infected with coronavirus disease 2019 (COVID-19) is high. However …
rate of the elderly infected with coronavirus disease 2019 (COVID-19) is high. However …
[HTML][HTML] Refining a non-invasive prediction model for neurosyphilis diagnosis by using immunoassay to detect serum anti-TP0435 (TP17) and TP0574 (TP47) IgG …
W Ke, C Ao, L Wang, X Zhang, J Shui, J Zhao… - Clinical Microbiology …, 2024 - Elsevier
Objectives Invasive lumbar puncture is the conventional method for diagnosing
neurosyphilis (NS). We investigated a non-invasive alternative method to detect serum …
neurosyphilis (NS). We investigated a non-invasive alternative method to detect serum …
[HTML][HTML] Continuing Education Activity
SK Jha, B Karna, MB Goodman - europepmc.org
Objectives: Identify the risk factors for contracting neurosyphilis. Assess the history and
physical findings suggestive of neurosyphilis. Apply evidence-based evaluation and …
physical findings suggestive of neurosyphilis. Apply evidence-based evaluation and …