Emergency Medicine

[Digitalization and artificial intelligence in orthopedics and traumatology].

In the course of digitalization it is becoming increasingly rare for medical documents to be handwri...

Detecting central hypovolemia in simulated hypovolemic shock by automated feature extraction with principal component analysis.

Assessment of the volume status by blood pressure (BP) monitoring is difficult, since baroreflex con...

Surgical Risk Is Not Linear: Derivation and Validation of a Novel, User-friendly, and Machine-learning-based Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) Calculator.

INTRODUCTION: Most risk assessment tools assume that the impact of risk factors is linear and cumula...

Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility.

Earlier we created a chemical hazard database via natural language processing of dossiers submitted ...

Predicting the Ability of Wounds to Heal Given Any Burn Size and Fluid Volume: An Analytical Approach.

The intrinsic relationship between fluid volume and open wound size (%) has not been previously exam...

Artificial intelligence can predict daily trauma volume and average acuity.

BACKGROUND: The goal of this study was to integrate temporal and weather data in order to create an ...

Mahalanobis Outier Removal for Improving the Non-Viable Detection on Human Injuries.

Machine learning techniques have been recently applied for discriminating between Viable and Non-Via...

Detecting Intracranial Hemorrhage with Deep Learning.

Initial results are reported on automated detection of intracranial hemorrhage from CT, which would ...

Predicting Mortality in the Surgical Intensive Care Unit Using Artificial Intelligence and Natural Language Processing of Physician Documentation.

The purpose of this study was to use natural language processing of physician documentation to predi...

Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay.

OBJECTIVES: Early prediction of undesired outcomes among newly hospitalized patients could improve p...

[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to c...

An intelligent algorithm for optimizing emergency department job and patient satisfaction.

Purpose Resilience engineering, job satisfaction and patient satisfaction were evaluated and analyze...

Snorkel MeTaL: Weak Supervision for Multi-Task Learning.

Many real-world machine learning problems are challenging to tackle for two reasons: (i) they involv...

Robotics in trauma and orthopaedics.

Recent advances and review of literature

The Long and Winding Triage Road.

[Advances in the research of application of artificial intelligence in burn field].

Artificial intelligence has been able to automatically learn and judge large-scale data to some exte...

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

In this paper, we propose a structural framework for population-based cancer epidemiology and evalua...

Investigating the Generalizability of the MultiFlow ® DNA Damage Assay and Several Companion Machine Learning Models With a Set of 103 Diverse Test Chemicals.

The in vitro MultiFlow DNA Damage assay multiplexes p53, γH2AX, phospho-histone H3, and polyploidiza...

Machine Learning Models for Prediction of Reinjury After Penetrating Trauma.

This study compares several machine learning models for prediction of reinjury after penetrating tra...

Origins of Robotic Surgery: From Skepticism to Standard of Care.

BACKGROUND AND OBJECTIVES: The uses of robotics in surgery were hypothesized as far back as 1967, bu...

Automatic Annotation Tool to Support Supervised Machine Learning for Scaphoid Fracture Detection.

The aim of this work is to develop and validate an automatic annotation tool for the detection and b...