Identifying and Reporting Dependent Adult abuse

Making Sense of Pharmacovigilance and Drug Adverse Event Reporting: Comparative Similarity Association Analysis Using AI Machine Learning Algorithms in Dogs and Cats.

Drug-associated adverse events cause approximately 30 billion dollars a year of added health care ex...

Symmetry of generalized rivalry network models determines patterns of interocular grouping in four-location binocular rivalry.

Previously, symmetry of network models has been proposed to account for interocular grouping during ...

Detecting substance-related problems in narrative investigation summaries of child abuse and neglect using text mining and machine learning.

BACKGROUND: State child welfare agencies collect, store, and manage vast amounts of data. However, t...

Robotic platform for microinjection into single cells in brain tissue.

Microinjection into single cells in brain tissue is a powerful technique to study and manipulate neu...

Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak.

Investments in biosecurity practices are made by producers to reduce the likelihood of introducing p...

Statistics versus machine learning: definitions are interesting (but understanding, methodology, and reporting are more important).

Performance of an artificial intelligence algorithm for reporting urine cytopathology.

BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automat...

Using machine learning-based lesion behavior mapping to identify anatomical networks of cognitive dysfunction: Spatial neglect and attention.

Previous lesion behavior studies primarily used univariate lesion behavior mapping techniques to map...

Management of Thyroid Nodules Seen on US Images: Deep Learning May Match Performance of Radiologists.

BackgroundManagement of thyroid nodules may be inconsistent between different observers and time con...

Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning.

Background Coronary CT angiography contains prognostic information but the best method to extract th...

Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation.

OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, gener...

Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility.

Background Risk stratification systems for thyroid nodules are often complicated and affected by low...

Integrating Bonded and Nonbonded Potentials in the Knowledge-Based Scoring Function for Protein Structure Prediction.

An accurate energy scoring function is crucial for protein structure prediction. Given the increasin...

Hemochromatosis in India: First Report of Whole Exome Sequencing With Review of the Literature.

BACKGROUND: Primary hemochromatosis is unusual in India. The homeostatic iron regulator (HFE) gene C...

Reporting and connecting cell type names and gating definitions through ontologies.

BACKGROUND: Human immunology studies often rely on the isolation and quantification of cell populati...

Assisting radiologists with reporting urgent findings to referring physicians: A machine learning approach to identify cases for prompt communication.

Radiologists are expected to expediently communicate critical and unexpected findings to referring c...

A gentle introduction to deep learning in medical image processing.

This paper tries to give a gentle introduction to deep learning in medical image processing, proceed...

Training recurrent neural networks robust to incomplete data: Application to Alzheimer's disease progression modeling.

Disease progression modeling (DPM) using longitudinal data is a challenging machine learning task. E...

Rapid LC-MS/MS quantification of cancer related acetylated polyamines in human biofluids.

Increased urinary acetylated polyamines (APs) are reported as cancer biomarkers in many studies. N,N...

A prototype of knowledge-based patient safety event reporting and learning system.

BACKGROUND: Patient falls, the most common safety events resulting in adverse patient outcomes, impo...

Using a Natural Language Processing and Machine Learning Algorithm Program to Analyze Inter-Radiologist Report Style Variation and Compare Variation Between Radiologists When Using Highly Structured Versus More Free Text Reporting.

PURPOSE: To use a natural language processing and machine learning algorithm to evaluate inter-radio...