AIMC Topic: United States
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Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.
Hepatology (Baltimore, Md.)
Dec 7, 2021
BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) mod...
Performance of Machine Learning Algorithms for Predicting Progression to Dementia in Memory Clinic Patients.
JAMA network open
Dec 1, 2021
IMPORTANCE: Machine learning algorithms could be used as the basis for clinical decision-making aids to enhance clinical practice.
Clinical application of robotic orthopedic surgery: a bibliometric study.
BMC musculoskeletal disorders
Nov 22, 2021
OBJECTIVES: The present study aimed to evaluate the status and trends of robotic orthopedic surgery in a clinical setting using bibliometrics.
What's Needed to Bridge the Gap Between US FDA Clearance and Real-world Use of AI Algorithms.
Academic radiology
Nov 20, 2021
Aedes-AI: Neural network models of mosquito abundance.
PLoS computational biology
Nov 19, 2021
We present artificial neural networks as a feasible replacement for a mechanistic model of mosquito abundance. We develop a feed-forward neural network, a long short-term memory recurrent neural network, and a gated recurrent unit network. We evaluat...
Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?
Gynecologic oncology
Nov 15, 2021
BACKGROUND: Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic va...
Achieving a 'Good AI Society': Comparing the Aims and Progress of the EU and the US.
Science and engineering ethics
Nov 12, 2021
Over the past few years, there has been a proliferation of artificial intelligence (AI) strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative a...
A Natural-Language-Processing-Based Procedure for Generating Distractors for Multiple-Choice Questions.
Evaluation & the health professions
Nov 9, 2021
One of the most challenging aspects of writing multiple-choice test questions is identifying plausible incorrect response options-i.e., distractors. To help with this task, a procedure is introduced that can mine existing item banks for potential dis...
Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.
Scientific reports
Nov 5, 2021
Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle an epidemiological process that evolves rapidly and is spatially heterogeneous. On the other hand, ma...
Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study.
Frontiers in public health
Nov 5, 2021
What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks? Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decade...
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