Domestic Violence

Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography.

Age estimation in dental radiographs Orthopantomography (OPG) is a medical imaging technique that physicians and pathologists utilize for disease identification and legal matters. For example, for estimating post-mortem interval, detecting child abuse, drug trafficking, and identifying an unknown body. Recent development in automated image processing models improved the age estimation's limited pr...

Development of practical triage methods for critical trauma patients: machine-learning algorithm for evaluating hybrid operation theatre entry of trauma patients (THETA).

PURPOSE: Hybrid operating rooms benefit patients with severe trauma but have a prerequisite of significant resources. This paper proposes a practical triage method to determine patients that should enter the hybrid operating room considering a limited availability of medical resources.

Utilization of sentiment analysis to assess and compare negative finding reporting in veterinary and human literature.

Publication bias and the decreased publication of trials with negative or non-significant results is a well-recognized problem in human and veterinary...

Social impact and governance of AI and neurotechnologies.

Advances in artificial intelligence (AI) and brain science are going to have a huge impact on society. While technologies based on those advances can ...

Comparison of state-of-the-art machine and deep learning algorithms to classify proximal humeral fractures using radiology text.

INTRODUCTION: Proximal humeral fractures account for a significant proportion of all fractures. Detailed accurate classification of the type and sever...

A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.

Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, im...

An image classification deep-learning algorithm for shrapnel detection from ultrasound images.

Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation r...

Predicting Perceived Reporting Complexity of Abdominopelvic Computed Tomography With Deep Learning.

OBJECTIVE: The purpose of this pilot study was to examine human and automated estimates of reporting complexity for computed tomography (CT) studies o...

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, ...

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico e...

Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.

BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. P...

Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies.

Rapid advances in automated methods for extracting large numbers of quantitative features from medical images have led to tremendous growth of publica...

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions.

Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of stron...

Power Intelligent Terminal Intrusion Detection Based on Deep Learning and Cloud Computing.

Numerous internal and external intrusion attacks have appeared one after another, which has become a major problem affecting the normal operation of t...

Reporting details of neuroimaging studies on individual traits prediction: A literature survey.

Using machine-learning tools to predict individual phenotypes from neuroimaging data is one of the most promising and hence dynamic fields in systems ...

Depression screening using a non-verbal self-association task: A machine-learning based pilot study.

BACKGROUND: Effective screening is important to combat the raising burden of depression and opens a critical time window for early intervention. Clini...

Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.

BACKGROUND: Lokomat therapy for gait rehabilitation has become increasingly popular. Most evidence suggests that Lokomat therapy is equally effective ...

LightEyes: A Lightweight Fundus Segmentation Network for Mobile Edge Computing.

Fundus is the only structure that can be observed without trauma to the human body. By analyzing color fundus images, the diagnosis basis for various ...

Deep Learning and Microscopic Imaging in the Nursing Process of Neurosurgery Operation.

Neurosurgery is mainly for the treatment of head trauma, cerebrovascular disease, brain tumors, and spinal cord disorders. These operations are diffic...

Deep Learning-Based Medical Information System in First Aid of Surgical Trauma.

The aim of this study was to explore the application of process reengineering integration in trauma first aid based on deep learning and medical infor...