Domestic Violence

TrendProbe: Time profile analysis of emerging contaminants by LC-HRMS non-target screening and deep learning convolutional neural network.

Peak prioritization is one of the key steps in non-target screening of environmental samples to direct the identification efforts to relevant and important features. Occurrence of chemicals is sometimes a function of time and their presence in consecutive days (trend) reveals important aspects such as discharges from agricultural, industrial or domestic activities. This study presents a validated ...

Understanding the potential of emerging digital technologies for improving road safety.

Each year, 1.35 million people are killed on the world's roads and another 20-50 million are seriously injured. Morbidity or serious injury from road traffic collisions is estimated to increase to 265 million people between 2015 and 2030. Current road safety management systems rely heavily on manual data collection, visual inspection and subjective expert judgment for their effectiveness, which is...

Is Blood Loss Greater in Elderly Patients under Antiplatelet or Anticoagulant Medication for Cervical Spine Injury Surgery? A Japanese Multicenter Survey.

INTRODUCTION: In elderly patients with cervical spinal cord injury, comorbidities such as cardiovascular and cerebrovascular diseases are common, with...

Robotics, automation, active electrode arrays, and new devices for cochlear implantation: A contemporary review.

In the last two decades, cochlear implant surgery has evolved into a minimally invasive, hearing preservation surgical technique. The devices used dur...

Clinical implications of the newly defined concept of ventilator-associated events in trauma patients.

PURPOSE: Ventilator-associated pneumonia is the most common nosocomial infection in patients with mechanical ventilation. In 2013, the new concept of ...

Deep Learning for Radiotherapy Outcome Prediction Using Dose Data - A Review.

Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and s...

Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation.

Background Use of artificial intelligence (AI) as a stand-alone reader for digital mammography (DM) or digital breast tomosynthesis (DBT) breast scree...

Opportunistic Osteoporosis Screening Using Chest Radiographs With Deep Learning: Development and External Validation With a Cohort Dataset.

Osteoporosis is a common, but silent disease until it is complicated by fractures that are associated with morbidity and mortality. Over the past few ...

Machine-Learning-Enabled Virtual Screening for Inhibitors of Lysine-Specific Histone Demethylase 1.

A machine learning approach has been applied to virtual screening for lysine specific demethylase 1 (LSD1) inhibitors. LSD1 is an important anti-cance...

Determination of multiple drugs of abuse in human urine using dispersive liquid-liquid microextraction and capillary electrophoresis with PDA detection.

A new method was developed for pre-concentration and determination of multiple drugs of abuse in human urine using dispersive liquid-liquid microextra...

Categorical Matrix Completion With Active Learning for High-Throughput Screening.

The recent advances in wet-lab automation enable high-throughput experiments to be conducted seamlessly. In particular, the exhaustive enumeration of ...

The development of "automated visual evaluation" for cervical cancer screening: The promise and challenges in adapting deep-learning for clinical testing: Interdisciplinary principles of automated visual evaluation in cervical screening.

There is limited access to effective cervical cancer screening programs in many resource-limited settings, resulting in continued high cervical cancer...

Robotic donor hepatectomy: A major breakthrough in living donor liver transplantation.

Living donation in many countries is the main resource of organs. Healthy, volunteering individuals deserve the highest safety standards possible in a...

A weakly supervised model for the automated detection of adverse events using clinical notes.

With clinical trials unable to detect all potential adverse reactions to drugs and medical devices prior to their release into the market, accurate po...

Overview of Explainable Artificial Intelligence for Prognostic and Health Management of Industrial Assets Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Surveys on explainable artificial intelligence (XAI) are related to biology, clinical trials, fintech management, medicine, neurorobotics, and psychol...

Assessment of the Cytotoxic Activity of Alcoholic Extract of on Breast Cancer Cell Line.

The spread of different types of cancer has been on a rise in the recent century. The use of chemical medications develops drug resistance and causes ...

Deep learning algorithm in detecting intracranial hemorrhages on emergency computed tomographies.

BACKGROUND: Highly accurate detection of intracranial hemorrhages (ICH) on head computed tomography (HCT) scans can prove challenging at high-volume c...

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.

Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitab...

Network analysis of trauma in patients with early-stage psychosis.

Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are...

Gender differences in under-reporting hiring discrimination in Korea: a machine learning approach.

OBJECTIVES: This study was conducted to examine gender differences in under-reporting hiring discrimination by building a prediction model for workers...