Latest AI and machine learning research in domestic violence for healthcare professionals.
BACKGROUND: State child welfare agencies collect, store, and manage vast amounts of data. However, they often do not have the right data, or the data is problematic or difficult to inform strategies to improve services and system processes. Considerable resources are required to read and code these text data. Data science and text mining offer potentially efficient and cost-effective strategies fo...
The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems. Here, we develop a deep learning algorithm that can accurately detect breast cancer on screening mammograms using an "end-to-end" training approach that efficiently leverages training datasets with either complete clinical annotation or only the...
Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently, the United States Preventative Services Task Forc...
In this work, computational compound screening strategies on the basis of two- and three-dimensional (2D and 3D) molecular representations were invest...
Investments in biosecurity practices are made by producers to reduce the likelihood of introducing pathogens such as porcine reproductive and respirat...
Influenza A viruses are one of the most significant viral groups globally with substantial impacts on human, domestic animal and wildlife health. Wild...
BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite ...
Diabetes is a global public health disease projected to affect 642 million adults by 2040, with about 75% residing in low- and middle-income countries...
Glaucoma is a chronic eye disease that leads to irreversible vision loss. The Cup-to-Disc Ratio (CDR) serves as the most important indicator for glauc...
New robotic systems have recently emerged to assist with peripheral lung access, but a robotic system for rigid bronchoscopy has yet to be developed. ...
Learning-to-rank, which is a machine-learning technique for information retrieval, was recently introduced to ligand-based virtual screening to reduce...
Toxic misfolded proteins potentially underly many neurodegenerative diseases, but individual targets which regulate these proteins and their downstrea...
The United States of America is fighting against one of its worst-ever drug crises. Over 900 people a week die from opioid- or heroin-related overdose...
BackgroundManagement of thyroid nodules may be inconsistent between different observers and time consuming for radiologists. An artificial intelligenc...
Although algebraic graph theory-based models have been widely applied in physical modeling and molecular studies, they are typically incompetent in th...
Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient w...
Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine l...
Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We appl...
OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analy...
Background Risk stratification systems for thyroid nodules are often complicated and affected by low specificity. Continual improvement of these syste...