Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work...
OBJECTIVE: Chronic inflammatory processes involving the vascular wall may induce atherosclerosis. Immune-inflammatory processes proceed throughout all stages of acute stroke. We investigated the association of three immune-inflammatory markers, namel...
Gan to kagaku ryoho. Cancer & chemotherapy
Dec 1, 2020
Robot-assisted laparoscopic surgery(RALS)for rectal cancer has been covered by National Health Insurance in Japan since April 2018. We launched RALS in our hospital in October 2019 and now report the short-term results(up to January 2020). Altogether...
European review for medical and pharmacological sciences
Dec 1, 2020
OBJECTIVE: Patients with acute severe and medical refractory ulcerative colitis have a high risk of postoperative complications after total abdominal colectomy (TAC). The objective of this retrospective study is to use machine learning to analyze and...
BACKGROUND: Internet search engine data, such as Google Trends, was shown to be correlated with the incidence of COVID-19, but only in several countries. We aim to develop a model from a small number of countries to predict the epidemic alert level i...
OBJECTIVES: We hypothesized that published performances of algorithms for artificial intelligence (AI) pneumothorax (PTX) detection in chest radiographs (CXRs) do not sufficiently consider the influence of PTX size and confounding effects caused by t...
The aim of this study is to develop an automated classification method for Brain Tumor Reporting and Data System (BT-RADS) categories from unstructured and structured brain magnetic resonance imaging (MR) reports. This retrospective study included 14...
OBJECTIVE: To compare the performance of machine learning models against the traditionally derived Combined Assessment of Risk Encountered in Surgery (CARES) model and the American Society of Anaesthesiologists-Physical Status (ASA-PS) in the predict...
We have developed a deep learning-based approach to improve image quality of single-shot turbo spin-echo (SSTSE) images of female pelvis. We aimed to compare the deep learning-based single-shot turbo spin-echo (DL-SSTSE) images of female pelvis with ...
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