Health Policy

Assessing the quality of sardine based on biogenic amines using a fuzzy logic model.

There is an increasing concern about the quality and quality assessment procedures of seafood. In the present study, a model to assess fish quality based on biogenic amine contents using fuzzy logic model (FLM) is proposed. The fish used was sardine (Sardinella sp.) where the production of eight biogenic amines was monitored over fifteen days of storage at 0, 3 and 10°C. Based on the results, hist...

Non-obvious correlations to disease management unraveled by Bayesian artificial intelligence analyses of CMS data.

OBJECTIVE: Given the availability of extensive digitized healthcare data from medical records, claims and prescription information, it is now possible to use hypothesis-free, data-driven approaches to mine medical databases for novel insight. The goal of this analysis was to demonstrate the use of artificial intelligence based methods such as Bayesian networks to open up opportunities for creation...

Deep learning architecture for air quality predictions.

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and ci...

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, spe...

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimed...

Joint amplitude MEMS based measurement platform for low cost and high accessibility telerehabilitation: Elbow case study.

This paper, presents an inertial and magnetic sensor based technological platform, intended for articular amplitude monitoring and telerehabilitation ...

Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification.

Embedding cost-sensitive factors into the classifiers increases the classification stability and reduces the classification costs for classifying high...

Iliac Limb Perigraft Access with Robotic Catheter Assistance for Type 2 Endoleak Embolization.

Retrograde perigraft access to the aneurysmal sac for type 2 endoleak embolization is a relevant alternative to standard transarterial and translumbar...

HPIDB 2.0: a curated database for host-pathogen interactions.

Identification and analysis of host-pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing mo...

Using machine learning to support healthcare professionals in making preauthorisation decisions.

BACKGROUND: Preauthorisation is a control mechanism that is used by Health Insurance Providers (HIPs) to minimise wastage of resources through the den...

Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting.

Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack...

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be m...

Erythropoiesis-stimulating Agents and Anemia in Patients with Non-dialytic Chronic Kidney Disease.

Anemia is common in patients with advanced chronic kidney disease (CKD). Though erythropoiesis-stimulating agents (ESAs) have been strongly endorsed i...

Intensification of degradation of methomyl (carbamate group pesticide) by using the combination of ultrasonic cavitation and process intensifying additives.

In the present work, the degradation of methomyl has been carried out by using the ultrasound cavitation (US) and its combination with H2O2, Fenton an...

Making Activity Recognition Robust against Deceptive Behavior.

Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to ...

Predictive modeling of structured electronic health records for adverse drug event detection.

BACKGROUND: The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilit...

A Data Quality Ontology for the Secondary Use of EHR Data.

The secondary use of EHR data for research is expected to improve health outcomes for patients, but the benefits will only be realized if the data in ...

Cost-Sensitive Local Binary Feature Learning for Facial Age Estimation.

In this paper, we propose a cost-sensitive local binary feature learning (CS-LBFL) method for facial age estimation. Unlike the conventional facial ag...

Feasibility of 30-day hospital readmission prediction modeling based on health information exchange data.

INTRODUCTION: Unplanned 30-day hospital readmission account for roughly $17 billion in annual Medicare spending. Many factors contribute to unplanned ...

Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.

Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurologic...