Domestic Violence

[Simultaneous determination of four opioids in urine by solid-phase extraction and derivatization coupled with gas chromatography-mass spectrometry].

Police officers currently use the colloidal gold rapid testing method to detect heroin in the urine of drug abusers, but the results are often rendered erroneous due to the presence of antitussive drugs, which contain opioids. The traditional manual liquid-liquid extraction method for urine testing has low efficiency and poor sensitivity, and hence, it fails to meet the requirements of the public ...

[Challenges of digitalization in trauma care].

The increasing digitalization of social life opens up new possibilities for modern health care. This article describes innovative application possibilities that could help to sustainably improve the treatment of severe injuries in the future with the help of methods such as big data, artificial intelligence, intelligence augmentation, and machine learning. For the successful application of these m...

[Digital OR].

BACKGROUND: Numerous processes are involved in the orthopedic and trauma surgery operating room (OR). Technical progress, particularly in the area of ...

Current Clinical Applications of Artificial Intelligence in Radiology and Their Best Supporting Evidence.

PURPOSE: Despite tremendous gains from deep learning and the promise of artificial intelligence (AI) in medicine to improve diagnosis and save costs, ...

Rhabdomyolysis in a Civil Aviation Pilot.

Rhabdomyolysis is a potentially fatal disease caused by trauma, infections, and toxins. Rhabdomyolysis has not been reported in Chinese civil aircrew...

[Artificial intelligence technology in cardiac auscultation screening for congenital heart disease: present and future].

The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent ...

A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learni...

Cost-effectiveness of Autonomous Point-of-Care Diabetic Retinopathy Screening for Pediatric Patients With Diabetes.

IMPORTANCE: Screening for diabetic retinopathy is recommended for children with type 1 diabetes (T1D) and type 2 diabetes (T2D), yet screening rates r...

Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study.

BACKGROUND: We examined the potential change in cancer detection when using an artificial intelligence (AI) cancer-detection software to triage certai...

[Artificial intelligence for cancer detection in breast cancer screening].

Artificial intelligence (AI) has the potential to increase quality and efficiency of breast cancer screening. Recent studies have provided comparative...

Combat medic testing of a novel monitoring capability for early detection of hemorrhage.

BACKGROUND: Current out-of-hospital protocols to determine hemorrhagic shock in civilian trauma systems rely on standard vital signs with military gui...

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate sc...

Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?

BACKGROUND: Machine-learning methods such as the Bayesian belief network, random forest, gradient boosting machine, and decision trees have been used ...

Machine-learning approaches to substance-abuse research: emerging trends and their implications.

PURPOSE OF REVIEW: To provide an accessible overview of some of the most recent trends in the application of machine learning to the field of substanc...

Assessment of a Deep Learning Algorithm for the Detection of Rib Fractures on Whole-Body Trauma Computed Tomography.

OBJECTIVE: To assess the diagnostic performance of a deep learning-based algorithm for automated detection of acute and chronic rib fractures on whole...

Risk assessment for intra-abdominal injury following blunt trauma in children: Derivation and validation of a machine learning model.

BACKGROUND: Computed tomography is the criterion standard for diagnosing intra-abdominal injury (IAI) but is expensive and risks radiation exposure. T...

A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs.

Chest radiographs are primarily employed for the screening of pulmonary and cardio-/thoracic conditions. Being undertaken at primary healthcare center...

Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening.

Chest radiographs are primarily employed for the screening of cardio, thoracic and pulmonary conditions. Machine learning based automated solutions ar...

Improved Classification of Medical Data Using Meta-Best Feature Selection.

Feature selection provides a useful method for reducing the size of large data sets while maintaining integrity, thereby improving the accuracy of neu...

Machine Learning Assisted Citation Screening for Systematic Reviews.

Evidence-based practice is highly dependent upon up-to-date systematic reviews (SR) for decision making. However, conducting and updating systematic r...