Latest AI and machine learning research in public health & policy for healthcare professionals.
Since its first outbreak, Coronavirus Disease 2019 (COVID-19) has been rapidly spreading worldwide and caused a global pandemic. Rapid and early detection is essential to contain COVID-19. Here, we first developed a deep learning (DL) integrated radiomics model for end-to-end identification of COVID-19 using CT scans and then validated its clinical feasibility. We retrospectively collected CT imag...
Health insurance and acute hospital-based claims have recently become available as real-world data after marketing in Japan and, thus, classification and prediction using the machine learning approach can be applied to them. However, the methodology used for the analysis of real-world data has been hitherto under debate and research on visualizing the patient journey is still inconclusive. So far,...
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatm...
Most biomedical datasets, including those of 'omics, population studies, and surveys, are rectangular in shape and have few missing data. Recently, th...
The prediction of hospital emergency room visits (ERV) for respiratory diseases after the outbreak of PM is of great importance in terms of public hea...
In recent years, public health emergencies have occurred frequently, posing a serious threat to the regional economy and the safety of people's lives ...
BACKGROUND: Mathematical modeling of vector-borne diseases and forecasting of epidemics outbreak are global challenges and big point of concern worldw...
The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. The ...
BACKGROUND: Accurate prognostication is crucial in treatment decisions made for men diagnosed with non-metastatic prostate cancer. Current models rely...
Smart healthcare has been applied in many fields such as disease surveillance and telemedicine, etc. However, there are some challenges for device dep...
The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus, initially identified in Wuhan (Hubei province, Ch...
To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we...
With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have ...
COVID-19 is threatening the health of the entire human population. In order to control the spread of the disease, epidemiological investigations shoul...
Applying state-of-the-art machine learning and natural language processing on approximately one million of teleconsultation records, we developed a tr...
BACKGROUND: In the United States, the rapidly evolving COVID-19 outbreak, the shortage of available testing, and the delay of test results present cha...
Estimation of the epidemiology curve for the COVID-19 pandemic can be a very computationally challenging task. Thus far, there have been some implemen...
OBJECTIVES: The outbreak of coronavirus disease 2019 (COVID-19) was first reported in December 2019. Until now, many drugs and methods have been used ...
Improving global health requires making current and future drugs more effective and affordable. While healthcare systems around the world are faced w...
PURPOSE: The purpose of this study was to develop an automated process to analyze multimedia content on Twitter during the COVID-19 outbreak and class...