Health Policy

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses.

The application of machine learning to predict high-cost patients: A performance-comparison of different models using healthcare claims data.

Our aim was to predict future high-cost patients with machine learning using healthcare claims data. We applied a random forest (RF), a gradient boosting machine (GBM), an artificial neural network (ANN) and a logistic regression (LR) to predict high-cost patients in the following year. Therefore, we exploited routinely collected sickness funds claims and cost data of the years 2016, 2017 and 2018...

Robotics and cybersurgery in ophthalmology: a current perspective.

Ophthalmology is one of the most enriched fields, allowing the domain of artificial intelligence to be part of its point of interest in scientific res...

Evaluation and prediction of irrigation water quality of an agricultural district, SE Nigeria: an integrated heuristic GIS-based and machine learning approach.

Poor irrigation water quality can mar agricultural productivity. Traditional assessment of irrigation water quality usually requires the computation o...

Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification.

A hyperspectral image (HSI), which contains a number of contiguous and narrow spectral wavelength bands, is a valuable source of data for ground cover...

Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era.

At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting C...

Vision-Based Efficient Robotic Manipulation with a Dual-Streaming Compact Convolutional Transformer.

Learning from visual observation for efficient robotic manipulation is a hitherto significant challenge in Reinforcement Learning (RL). Although the c...

Considerations for Creating a Restricted Data Environment with Complete Primary Care Electronic Medical Record Data.

Background: Historically, primary care databases have been limited to subsets of the full electronic medical record (EMR) data to maintain privacy. Wi...

Wireless Link Selection Methods for Maritime Communication Access Networks-A Deep Learning Approach.

In recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widesprea...

Remote Sensing and Nonlinear Auto-regressive Neural Network (NARNET) Based Surface Water Chemical Quality Study: A Spatio-Temporal Hybrid Novel Technique (STHNT).

In recent days, the quality of water in inland water bodies has been threatened by various natural and anthropogenic activities. Henceforth, the conti...

A deep learning platform to assess drug proarrhythmia risk.

Drug safety initiatives have endorsed human iPSC-derived cardiomyocytes (hiPSC-CMs) as an in vitro model for predicting drug-induced cardiac arrhythmi...

Toward the Internet of Medical Things: Architecture, trends and challenges.

In recent years, the growing pervasiveness of wearable technology has created new opportunities for medical and emergency rescue operations to protect...

End-to-End One-Shot Path-Planning Algorithm for an Autonomous Vehicle Based on a Convolutional Neural Network Considering Traversability Cost.

Path planning plays an important role in navigation and motion planning for robotics and automated driving applications. Most existing methods use ite...

Case Study: Improving the Quality of Dairy Cow Reconstruction with a Deep Learning-Based Framework.

Three-dimensional point cloud generation systems from scanning data of a moving camera provide extra information about an object in addition to color....

An autonomous decision-making framework for gait recognition systems against adversarial attack using reinforcement learning.

Gait identification based on Deep Learning (DL) techniques has recently emerged as biometric technology for surveillance. We leveraged the vulnerabili...

Cost-effectiveness analysis of revisional Roux-en-Y gastric bypass: laparoscopic vs. robot assisted.

There is controversy over the possible advantages of the robotic technology in revisional bariatric surgery. The aim of this study is to report the ex...

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry.

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowi...

Reinforcement learning for robust stabilization of nonlinear systems with asymmetric saturating actuators.

We study the robust stabilization problem of a class of nonlinear systems with asymmetric saturating actuators and mismatched disturbances. Initially,...

Combining deep learning and crowd-sourcing images to predict housing quality in rural China.

Housing quality is essential to human well-being, security and health. Monitoring the housing quality is crucial for unveiling the socioeconomic devel...

Developing Low-Cost Mobile Device and Apps for Accurate Skin Spectrum Measurement via Low-Cost Spectrum Sensors and Deep Neural Network Technology.

In recent years, skin spectral information has been gradually applied in various fields, such as the cosmetics industry and clinical medicine. However...