Emergency Medicine

Robot-assisted flexible needle insertion using universal distributional deep reinforcement learning.

PURPOSE: Flexible needle insertion is an important minimally invasive surgery approach for biopsy and radio-frequency ablation. This approach can minimize intraoperative trauma and improve postoperative recovery. We propose a new path planning framework using multi-goal deep reinforcement learning to overcome the difficulties in uncertain needle-tissue interactions and enhance the robustness of ro...

Meteorological factors for subarachnoid hemorrhage in the greater Düsseldorf area revisited: a machine learning approach to predict the probability of admission of patients with subarachnoid hemorrhage.

BACKGROUND: Reported data regarding the relation between the incidence of spontaneous subarachnoid hemorrhage (SAH) and weather conditions are conflicting and do so far not allow prognostic models.

An Overview of Machine Learning and Big Data for Drug Toxicity Evaluation.

Drug toxicity evaluation is an essential process of drug development as it is reportedly responsible for the attrition of approximately 30% of drug ca...

Distributed deep learning across multisite datasets for generalized CT hemorrhage segmentation.

PURPOSE: As deep neural networks achieve more success in the wide field of computer vision, greater emphasis is being placed on the generalizations of...

Fully Automated Segmentation Algorithm for Hematoma Volumetric Analysis in Spontaneous Intracerebral Hemorrhage.

Background and Purpose- Hematoma volume measurements influence prognosis and treatment decisions in patients with spontaneous intracerebral hemorrhage...

Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: a Review.

MOTIVATION: Emergency Departments' (ED) modern triage systems implemented worldwide are solely based upon medical knowledge and experience. This is a ...

Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach.

Emergency departments (EDs) play a vital role in the whole healthcare system as they are the first point of care in hospitals for urgent and criticall...

Human-mimetic soft robot joint for shock absorption through joint dislocation.

This paper presents a human-mimetic manipulator capable of shock absorption by using dislocation at the soft joint. A one degree-of-freedom (DOF) soft...

Machine Learning-Based Forecast of Hemorrhagic Stroke Healthcare Service Demand considering Air Pollution.

This study aimed to forecast the pattern of the demand for hemorrhagic stroke healthcare services based on air quality and machine learning. Hemorrhag...

Machine-learned analysis of side-differences in odor identification performance.

A right-left dichotomy of olfactory processes has been recognized on several levels of the perception or processing of olfactory input. On a clinical ...

A Gradient Boosting Machine Learning Model for Predicting Early Mortality in the Emergency Department Triage: Devising a Nine-Point Triage Score.

BACKGROUND: Emergency departments (ED) are becoming increasingly overwhelmed, increasing poor outcomes. Triage scores aim to optimize the waiting time...

Multivariate modeling of engineered nanomaterial features associated with developmental toxicity.

Despite the increasing prevalence of engineered nanomaterials (ENMs) in consumer products, their toxicity profiles remain to be elucidated. ENM physic...

Increasing Cardiovascular Data Sampling Frequency and Referencing It to Baseline Improve Hemorrhage Detection.

UNLABELLED: We hypothesize that knowledge of a stable personalized baseline state and increased data sampling frequency would markedly improve the abi...

Drainage Collection After Endoscopic-Assisted Transaxillary Dual-Plane Augmentation Mammaplasty Using Cold or Electrosurgical Separation of Interpectoral Space.

BACKGROUND: Endoscopic transaxillary augmentation mammaplasty breast augmentation offers several advantages over other augmentation methods. Nonethele...

Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology.

Toxicologic pathology is transitioning from analog to digital methods. This transition seems inevitable due to a host of ongoing social and medical te...

Association between Blood Pressure after Haemodynamic Resuscitation in the Prehospital Setting and 28-Day Mortality in Septic Shock.

OBJECTIVE: Septic shock results in a decreased blood pressure (BP) leading to organ failure. The haemodynamic resuscitation aims at restoring the BP t...

Machine learning for prediction of septic shock at initial triage in emergency department.

BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or ME...

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department.

BackgroundThe performance of a deep learning (DL) algorithm should be validated in actual clinical situations, before its clinical implementation.Purp...

LiSep LSTM: A Machine Learning Algorithm for Early Detection of Septic Shock.

Sepsis is a major health concern with global estimates of 31.5 million cases per year. Case fatality rates are still unacceptably high, and early dete...

Fixation of intracapsular fracture of the femoral neck using combined peripheral nerve blocks and transthoracic echocardiography in a patient with severe obstructive hypertrophic cardiomyopathy: a case report.

BACKGROUND: Hypertrophic obstructive cardiomyopathy (HOCM) is a type of hypertrophic cardiomyopathy associated with left ventricular outflow tract ste...