Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea.

This paper deals with time series analysis for COVID-19 in South Korea. We adopt heterogeneous autoregressive (HAR) time series models and discuss the statistical inference for various COVID-19 data. Seven data sets such as cumulative confirmed (CC) case, cumulative recovered (CR) case and cumulative death (CD) case as well as recovery rate, fatality rate and infection rates for 14 and 21 days are handled for the statistical analysis.

A case of sigmoid colon tuberculosis mimicking colon cancer.

Tuberculosis of the sigmoid colon is a rare disorder. An 80-year-old man visited Bongseng Memorial Hospital for medical examination. A colonoscopy was performed, and a lesion in the sigmoid colon that was suspected to be colon cancer was found.