Domestic Violence

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 m...

Suicide Risk Prediction in Clinical Settings-Additional Considerations for Face-to-Face Screening and Machine Learning Approaches.

Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts.

Occlusion-based saliency maps (OBSMs) are one of the approaches for interpreting decision-making pro...

Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?

BACKGROUND: The health crisis resulting from the global COVID-19 pandemic highlighted more than ever...

Comparison of radiologist versus natural language processing-based image annotations for deep learning system for tuberculosis screening on chest radiographs.

Although natural language processing (NLP) can rapidly extract disease labels from radiology reports...

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 ...

Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa.

BACKGROUND: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last ...

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 s...

Clinical Machine Learning Modeling Studies: Methodology and Data Reporting.

Joint optic disk and cup segmentation for glaucoma screening using a region-based deep learning network.

OBJECTIVES: To develop and validate an end-to-end region-based deep convolutional neural network (R-...

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 ...

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 ...

Proposing Causal Sequence of Death by Neural Machine Translation in Public Health Informatics.

Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United States. ...

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colo...

Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment.

Background Deep learning (DL) algorithms could improve the classification of ovarian tumors assessed...

A New Approach for Abnormal Human Activities Recognition Based on ConvLSTM Architecture.

Recognizing various abnormal human activities from video is very challenging. This problem is also g...

Pros and Cons of Applying Deep Learning Automatic Scan-Range Adjustment to Low-Dose Chest CT in Lung Cancer Screening Programs.

Machine learning approach to identify adverse events in scientific biomedical literature.

Monitoring the occurrence of adverse events in the scientific literature is a mandatory process in d...

Prior information-based high-resolution tomography image reconstruction from a single digitally reconstructed radiograph.

Tomography images are essential for clinical diagnosis and trauma surgery, allowing doctors to under...

Multi-Task Fusion for Improving Mammography Screening Data Classification.

Machine learning and deep learning methods have become essential for computer-assisted prediction in...

Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.

Background Artificial intelligence (AI) has shown promising results for cancer detection with mammog...