Sexual Assault

Predicting Post-Concussion Symptom Recovery in Adolescents Using a Novel Artificial Intelligence.

This pilot study explores the possibility of predicting post-concussion symptom recovery at one week post-injury using only objective diffusion tensor imaging (DTI) data inputs to a novel artificial intelligence (AI) system composed of Genetic Fuzzy Trees (GFT). Forty-three adolescents age 11 to 16 years with either mild traumatic brain injury or traumatic orthopedic injury were enrolled on presen...

Artificial Intelligence Image-Assisted Knee Ligament Trauma Repair Efficacy Analysis and Postoperative Femoral Nerve Block Analgesia Effect Research.

OBJECTIVE: To analyze artificial intelligence image-assisted knee ligament injury repair and femoral nerve block analgesia after surgery.

A Rare Case of Familial Neurogenic Diabetes Insipidus in a 22-Year-Old Man.

OBJECTIVE: Diabetes insipidus (DI) can be classified into 2 types: central/neurogenic DI and nephrogenic DI. Most cases of central DI occur after brai...

Automatic measurement of pressure ulcers using Support Vector Machines and GrabCut.

BACKGROUND AND OBJECTIVE: Pressure ulcers are regions of trauma caused by a continuous pressure applied to soft tissues between a bony prominence and ...

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) pr...

Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet.

BACKGROUND: Diagnosis of rib fractures plays an important role in identifying trauma severity. However, quickly and precisely identifying the rib frac...

The opportunities and challenges of machine learning in the acute care setting for precision prevention of posttraumatic stress sequelae.

Personalized medicine is among the most exciting innovations in recent clinical research, offering the opportunity for tailored screening and manageme...

The niche of artificial intelligence in trauma and emergency medicine.

Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification.

Background and purpose - Classification of ankle fractures is crucial for guiding treatment but advanced classifications such as the AO Foundation/Ort...

Prediction of severe chest injury using natural language processing from the electronic health record.

INTRODUCTION: Trauma injury severity scores are currently calculated retrospectively from the electronic health record (EHR) using manual annotation b...

Hierarchical fracture classification of proximal femur X-Ray images using a multistage Deep Learning approach.

PURPOSE: Suspected fractures are among the most common reasons for patients to visit emergency departments and often can be difficult to detect and an...

Traffic Crash Severity Prediction-A Synergy by Hybrid Principal Component Analysis and Machine Learning Models.

The accurate prediction of road traffic crash (RTC) severity contributes to generating crucial information, which can be used to adopt appropriate mea...

Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?

BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascular, trauma, and orthopaedic surgery have rendered...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alc...

Diverse Applications of Artificial Intelligence in Neuroradiology.

Recent advances in artificial intelligence (AI) and deep learning (DL) hold promise to augment neuroimaging diagnosis for patients with brain tumors a...

Musculoskeletal trauma imaging in the era of novel molecular methods and artificial intelligence.

Over the past decade rapid advancements in molecular imaging (MI) and artificial intelligence (AI) have revolutionized traditional musculoskeletal rad...

Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy.

The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour...

Toward a hemorrhagic trauma severity score: fusing five physiological biomarkers.

BACKGROUND: To introduce the Hemorrhage Intensive Severity and Survivability (HISS) score, based on the fusion of multi-biomarker data; glucose, lacta...

Convolution neural network for effective burn region segmentation of color images.

BACKGROUND: Burn injuries are one of the most severe forms of wounds and trauma across the globe. Automated burn diagnosis methods are needed to provi...

Artificial intelligence in trauma systems.

Local trauma care and regional trauma systems are data-rich environments that are amenable to machine learning, artificial intelligence, and big-data ...