Hospital-Based Medicine

Utilizing graph machine learning within drug discovery and development.

Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the context of drug discovery and development...

[Comparison of single incision robot-assisted laparoscopic radical prostatectomy with and without extraperitoneal special channel device].

To compare the clinical effects of single-incision robot-assisted laparoscopic radical prostatectomy (RARP) with and without extraperitoneal special channel device. The clinical data of 70 patients who had undergone RARP in the Robotic Minimally Invasive Surgery Center of Sichuan Provincial People's Hospital from September 2020 to February 2021 were analyzed retrospectively, including 29 cases w...

Development and Validation of a Machine Learning-Based Decision Support Tool for Residency Applicant Screening and Review.

PURPOSE: Residency programs face overwhelming numbers of residency applications, limiting holistic review. Artificial intelligence techniques have bee...

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of is increasing year by year, posing a sev...

Exploring Features Contributing to the Early Prediction of Sepsis Using Machine Learning.

The increasing availability of electronic health records and administrative data and the adoption of computer-based technologies in healthcare have si...

Artificial Intelligence-assisted Prostate Cancer Diagnosis: Radiologic-Pathologic Correlation.

The classic prostate cancer (PCa) diagnostic pathway that is based on prostate-specific antigen (PSA) levels and the findings of digital rectal examin...

Radiomics in Oncology: A Practical Guide.

Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, a...

[Application of digital medical technology in hepatopancreatobiliary surgery:20 years' retrospective review and prospect].

Digital medicine has played a vital role in promoting the development of hepatobiliary and pancreatic surgery of China.The multidisciplinary integrati...

[Da Vinci robot-assisted pylorus and vagus nerve-preserving partial gastrectomy for gastric cancer].

To investigate the safety and feasibility of Da Vinci robot-assisted pylorus and vagus nerve-preserving partial gastrectomy for gastric cancer. In t...

Machine learning for initial insulin estimation in hospitalized patients.

OBJECTIVE: The study sought to determine whether machine learning can predict initial inpatient total daily dose (TDD) of insulin from electronic heal...

Extraperitoneal Single-Port Robot-Assisted Radical Prostatectomy.

Robot-assisted radical prostatectomy (RARP) is currently the standard minimally invasive procedure for the surgical management of localized prostate c...

Artificial neural network prediction of same-day discharge following primary total knee arthroplasty based on preoperative and intraoperative variables.

AIMS: This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day di...

An artificial neural network model to predict the mortality of COVID-19 patients using routine blood samples at the time of hospital admission: Development and validation study.

BACKGROUND:: In a pandemic situation (e.g., COVID-19), the most important issue is to select patients at risk of high mortality at an early stage and ...

[Single-center experience of robot-assisted laparoscopic nephron-sparing surgery for giant renal hamartoma].

The clinical data of 22 patients with giant renal hamartoma in Zhejiang Provincial People's Hospital who underwent robot-assisted laparoscopic nephron...

Predicting the Need For Vasopressors in the Intensive Care Unit Using an Attention Based Deep Learning Model.

BACKGROUND: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose o...

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.

OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a mode...

Improving the delivery of palliative care through predictive modeling and healthcare informatics.

OBJECTIVE: Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, ma...

Predicting ventilator-associated pneumonia with machine learning.

Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifyi...

[Robot-assisted nephroureterectomy requiring no robot redocking or patient repositioning: experience from a single center with 62 cases].

To examine a new technique of robot-assisted nephroureterectomy without robot reldocking or patient repositioning. Patients diagnosed as upper tract...

Gynecological Surgery and Machine Learning: Complications and Length of Stay Prediction.

In this study we are developing predictive models for a length of stay after a gynecological surgery, complications and the length of the surgery usin...