Domestic Violence

Chest X-ray-based opportunistic screening of sarcopenia using deep learning.

BACKGROUND: Early detection and management of sarcopenia is of clinical importance. We aimed to deve...

Developing a deep learning natural language processing algorithm for automated reporting of adverse drug reactions.

The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and ri...

Application of deep learning-based diagnostic systems in screening asymptomatic COVID-19 patients among oversea returnees.

INTRODUCTION: Our study aimed to investigate the performance of deep learning (DL)-based diagnostic ...

Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study.

BACKGROUND: Opportunely screening for diabetes is crucial to reduce its related morbidity, mortality...

Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system.

OBJECTIVES: To compare the diagnostic performance of a novel deep learning (DL) method based on T2-w...

What place for intelligent automation and artificial intelligence to preserve and strengthen vigilance expertise in the face of increasing declarations?

In 2018, the "Ateliers de Giens" (Giens Workshops) devoted a workshop to artificial intelligence (AI...

Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma.

Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to ...

Pterygium Screening and Lesion Area Segmentation Based on Deep Learning.

A two-category model and a segmentation model of pterygium were proposed to assist ophthalmologists ...

Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.

Rapid detection of intracranial haemorrhage (ICH) is crucial for assessing patients with neurologica...

Robust deep learning-based forward dose calculations for VMAT on the 1.5T MR-linac.

In this work we present a framework for robust deep learning-based VMAT forward dose calculations fo...

A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay.

INTRODUCTION: Trauma patients have diverse resource needs due to variable mechanisms and injury patt...

Deffini: A family-specific deep neural network model for structure-based virtual screening.

Deep learning-based virtual screening methods have been shown to significantly improve the accuracy ...

Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.

Comparing a family structure to a company, one can often think of parents as leaders and adolescents...

Beyond the : Deep Learning Model for Risk-Based Breast Cancer Screening.

Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis.

Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in practice ...

MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery.

Molecular docking tools are regularly used to computationally identify new molecules in virtual scre...

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy....

Assessment of Radiology Artificial Intelligence Software: A Validation and Evaluation Framework.

Artificial intelligence (AI) software in radiology is becoming increasingly prevalent and performanc...

A Natural Language Processing and Machine Learning Approach to Identification of Incidental Radiology Findings in Trauma Patients Discharged from the Emergency Department.

STUDY OBJECTIVE: Patients undergoing diagnostic imaging studies in the emergency department (ED) com...

Deep Learning Hybrid Techniques for Brain Tumor Segmentation.

Medical images play an important role in medical diagnosis and treatment. Oncologists analyze images...

Clinical safety and efficacy of a fully automated robot for magnetic resonance imaging-guided breast biopsy.

BACKGROUND: Magnetic resonance imaging (MRI)-guided biopsies are an accurate, but technically challe...