Domestic Violence

A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter.

BACKGROUND: Emotions after surviving cancer can be complicated. The survivors may have gained new strength to continue life, but some of them may begin to deal with complicated feelings and emotional stress due to trauma and fear of cancer recurrence. The widespread use of Twitter for socializing has been the alternative medium for data collection compared to traditional studies of mental health, ...

Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis.

BACKGROUND: Healthcare is a rapidly expanding area of application for Artificial Intelligence (AI). Although there is considerable excitement about its potential, there are also substantial concerns about the negative impacts of these technologies. Since screening and diagnostic AI tools now have the potential to fundamentally change the healthcare landscape, it is important to understand how thes...

Moderate to severe leukocytosis with vasopressor use is associated with increased mortality in trauma patients.

BACKGROUND: Leukocytosis is a rise in white blood cell (WBC) count and clinical outcomes of moderate to severe leukocytosis in trauma patients have no...

Shoulder hydrodilatation for primary, post-traumatic and post-operative adhesive capsulitis.

BACKGROUND: Adhesive capsulitis (frozen shoulder) is characterised by pain and loss of range of motion of the glenohumeral joint. It can be present as...

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis.

Screening for prostate cancer relies on the serum prostate-specific antigen test, which provides a high rate of false positives (80%). This results in...

Iterative reconstruction and deep learning algorithms for enabling low-dose computed tomography in midfacial trauma.

OBJECTIVES: The objective of this study was to quantitatively assess the image quality of Advanced Modeled Iterative Reconstruction (ADMIRE) and the P...

Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches.

Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), an...

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...

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 ...

Digital Gaming Interventions in Psychiatry: Evidence, Applications and Challenges.

Human evolution has regularly intersected with technology. Digitalization of various services has brought a paradigm shift in consumerism. Treading th...

Population-Based Screening for Endometrial Cancer: Human vs. Machine Intelligence.

Incidence and mortality rates of endometrial cancer are increasing, leading to increased interest in endometrial cancer risk prediction and stratifica...

Automated estimation of echocardiogram image quality in hospitalized patients.

We developed a machine learning model for efficient analysis of echocardiographic image quality in hospitalized patients. This study applied a machine...

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...

Thyroid nodules risk stratification through deep learning based on ultrasound images.

PURPOSE: Clinically, the risk stratification of thyroid nodules is usually used to formulate the next treatment plan. The American College of Radiolog...

Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.

INTRODUCTION: Studies addressing the development and/or validation of diagnostic and prognostic prediction models are abundant in most clinical domain...

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 Hidden Pandemic of Family Violence During COVID-19: Unsupervised Learning of Tweets.

BACKGROUND: Family violence (including intimate partner violence/domestic violence, child abuse, and elder abuse) is a hidden pandemic happening along...

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...