Purpose: A reduction in cancer services during the coronavirus disease of 2019 pandemic has affected cancer diagnoses. The purpose of this study is to...Read more

Background: To better understand the different clinical phenotypes across the disease spectrum in patients with COVID-19 using an unsupervised machine...Read more

Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 in resource-scarce countries. In this study, we ap...Read more

PURPOSE: To evaluate the performance of a deep learning (DL) algorithm for the detection of COVID-19 on chest radiographs (CXR). MATERIALS AND METHODS...Read more

Purpose: The coronavirus disease 2019 (COVID-19) has evolved into a worldwide pandemic. CT although sensitive in detecting changes suffers from poor s...Read more

Objectives: To develop: (1) two validated risk prediction models for coronavirus disease-2019 (COVID-19) positivity using readily available parameters...Read more

自上世紀八十年代醫學影像技術數碼化以來，為人工智能的應用奠定了基礎。香港大學放射診斷學系一直致力於研究將機器學習和人工智能技術應用於醫學影像診斷。他們進行了臨床研究，以確保患者獲得最佳效果，例如使用AI自動診斷眼部疾病以及探討放射科醫生與人工智能之間的互動。人工智能的應用不僅影響醫生，還直接影響患者...Read more

Data privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward...Read more

Methods to recover high-quality computed tomography (CT) images in low-dose cases will be of great benefit. To reach this goal, sparse-data subsamplin...Read more