Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
Synchronous cancers should be first evaluated at high-volume referral oncological centers. Multidisciplinary evaluation, as the first step of multimodal treatment strategy, is also a way to select candidates fit for surgical resections. Concurrent minimally invasive approaches are a safe and effective option that may result in long-term control of the disease. Robot-assisted surgery allows obtaini...
BACKGROUND: Many factors involved in the onset and clinical course of the ongoing COVID-19 pandemic are still unknown. Although big data analytics and artificial intelligence are widely used in the realms of health and medicine, researchers are only beginning to use these tools to explore the clinical characteristics and predictive factors of patients with COVID-19.
The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity a...
This study aimed to investigate the needs of medical users of telemedicine robots to encourage international cooperation and development. As the use...
As the prevalence of obesity climbs, dosing of antimicrobials, particularly cephalosporins, is becoming a greater challenge for clinicians. Data are ...
To demonstrate two distinct methods for adopting the single-port (SP) robotic surgery system for robotic-assisted laparoscopic prostatectomy (RALP) b...
OBJECTIVE: To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improv...
The prediction of the liver failure (LF) and its proper diagnosis would lead to a reduction in the complications of the disease and prevents the progr...
BACKGROUND: COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapid human-to-human transmission of SARS-CoV-2, many ...
Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the ...
BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascular, trauma, and orthopaedic surgery have rendered...
BACKGROUND: Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs...
Electronic health records (EHRs) often suffer missing values, for which recent advances in deep learning offer a promising remedy. We develop a deep l...
We evaluated the efficacy of rehabilitation therapy with Hybrid Assistive Limb® (HAL; hereafter HAL therapy) in three patients diagnosed with sporadic...
BACKGROUND: Acute kidney injury (AKI) carries a poor prognosis. Its incidence is increasing in the intensive care unit (ICU). Our purpose in this stud...
As high-throughput approaches in biological and biomedical research are transforming the life sciences into information-driven disciplines, modern ana...
Since 2007, we have gradually been building up infrastructure for digital pathology, starting with a whole slide scanner park to build up a digital ar...
BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stro...
To perform a systematic review and meta-analysis comparing the outcomes of robotic-assisted laparoscopic extravesical ureteric reimplantation (RALUR) ...
A digital medical health system named Tianxia120 that can provide patients and hospitals with "one-step service" is proposed in this paper. Evolving f...