Domestic Violence

Identifying the Long-term Brain Changes Associated With Childhood Trauma Exposure Using Data-Driven Machine Learning Techniques.

Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: A multicenter study.

BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have recently shown the ability to predict admission volume, acuity, and operative needs at a single trauma center with very high reliability. This model has not been tested in a multicenter model with differing climate and geography. We hypothesize that an ANN can accurately predict trauma admission volume...

Comparison of Machine Learning Optimal Classification Trees With the Pediatric Emergency Care Applied Research Network Head Trauma Decision Rules.

IMPORTANCE: Computed tomographic (CT) scanning is the standard for the rapid diagnosis of intracranial injury, but it is costly and exposes patients t...

Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning.

Glaucoma is the second leading cause of blindness worldwide. This paper proposes an automated glaucoma screening method using retinal fundus images vi...

1D Convolutional Neural Networks for Estimation of Compensatory Reserve from Blood Pressure Waveforms.

We propose a Deep Convolutional Neural Network (CNN) architecture for computing a Compensatory Reserve Metric (CRM) for trauma victims suffering from ...

A Machine Learning Strategy for Autism Screening in Toddlers.

OBJECTIVE: Autism spectrum disorder (ASD) screening can improve prognosis via early diagnosis and intervention, but lack of time and training can dete...

Combining Natural Language Processing of Electronic Medical Notes With Administrative Data to Determine Racial/Ethnic Differences in the Disclosure and Documentation of Military Sexual Trauma in Veterans.

BACKGROUND: Despite national screening efforts, military sexual trauma (MST) is underreported. Little is known of racial/ethnic differences in MST rep...

A Deep Learning-Based Decision Support Tool for Precision Risk Assessment of Breast Cancer.

PURPOSE: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed to standardize mammographic reporting to assess cancer risk and ...

Development of an automatic classifier for the prediction of hearing impairment from industrial noise exposure.

The ISO-1999 [(2013). International Organization for Standardization, Geneva, Switzerland] standard is the most commonly used approach for estimating ...

Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.

OBJECTIVE: Alcohol misuse is present in over a quarter of trauma patients. Information in the clinical notes of the electronic health record of trauma...

Virtual Screening Meets Deep Learning.

BACKGROUND: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the ...

DeepScreening: a deep learning-based screening web server for accelerating drug discovery.

Deep learning contributes significantly to researches in biological sciences and drug discovery. Previous studies suggested that deep learning techniq...

Animal Bite in a 6-month-old Child and Facial Injury with Associated Unusual Nasal Injury: Management of Injuries along with 1-year Follow-up.

UNLABELLED: In children, accidental injuries (AI) are the most common cause of major trauma. Although rare, nonaccidental injuries (NAI) can also caus...

[Digitalization and artificial intelligence in orthopedics and traumatology].

In the course of digitalization it is becoming increasingly rare for medical documents to be handwritten. As a result, digitalization has already beco...

[Big data and deep learning in preventive and rehabilitation medicine].

The digitalization in medicine has led to almost universal availability of information to different healthcare professionals and accelerated clinical ...

MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized meth...

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 artificial neural network (ANN) to predict trauma ...

A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI.

Mild traumatic brain injury is a growing public health problem with an estimated incidence of over 1.7 million people annually in US. Diagnosis is bas...

Barriers to staff reporting adverse incidents in NHS hospitals.

Our study assessed barriers to reporting adverse incidents (AIs). Adverse incident reporting (AIR), although it is a pillar of risk management, has a ...

Robotics in trauma and orthopaedics.

Recent advances and review of literature