Health Policy

A review of machine learning in obesity.

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning provides sophisticated and elegant tools to describe, classify and predict obesity-related risks and outcomes. Here, we review machine learning methods th...

Providing Healthcare-as-a-Service Using Fuzzy Rule Based Big Data Analytics in Cloud Computing.

With advancements in information and communication technology, there is a steep increase in the remote healthcare applications in which patients can get treatment from the remote places also. The data collected about the patients by remote healthcare applications constitute big data because it varies with volume, velocity, variety, veracity, and value. To process such a large collection of heterog...

[Position Paper of The AG Digital Health DNVF on Digital Health Applications: Framework Conditions For Use in Health Care, Structural Development and Science].

The term "digital health" is currently the most comprehensive term that includes all information and communication technologies in healthcare, includi...

Cost-Sensitive Feature Selection by Optimizing F-Measures.

Feature selection is beneficial for improving the performance of general machine learning tasks by extracting an informative subset from the high-dime...

Clickstream Analysis for Crowd-Based Object Segmentation with Confidence.

With the rapidly increasing interest in machine learning based solutions for automatic image annotation, the availability of reference annotations for...

Estimation of stress distribution in ferromagnetic tensile specimens using low cost eddy current stress measurement system and BP neural network.

Estimation of the stress distribution in ferromagnetic components is very important for evaluating the working status of mechanical equipment and impl...

Vitamin C evaluation in foods for infants and young children by a rapid and accurate analytical method.

The validation of a rapid, precise (RSD < 4.6%), reliable and sensitive (LOD = 0.026 µg/mL) liquid chromatography method for vitamin C quantification ...

Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare.

The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major ...

Web-Enabled Distributed Health-Care Framework for Automated Malaria Parasite Classification: an E-Health Approach.

Web-enabled e-healthcare system or computer assisted disease diagnosis has a potential to improve the quality and service of conventional healthcare d...

Comparative Analysis of the Cytology and Transcriptomes of the Cytoplasmic Male Sterility Line H276A and Its Maintainer Line H276B of Cotton (Gossypium barbadense L.).

In this study, the tetrad stage of microspore development in a new cotton ( L.) cytoplasmic male sterility (CMS) line, H276A, was identified using par...

DanHong injection targets endothelin receptor type B and angiotensin II receptor type 1 in protection against cardiac hypertrophy.

Cardiac hypertrophy (CH) is an independent risk factor for cardiovascular diseases (CVDs). Mitigating or preventing CH is the most effective strategy ...

Mobile Robotic Telepresence Solutions for the Education of Hospitalized Children.

Hospitalization affects children's school attendance, resulting in poor academic and sociodevelopmental outcomes. The increasing ubiquity of mobile an...

Kinase inhibitor screening using artificial neural networks and engineered cardiac biowires.

Kinase inhibitors are often used as cancer targeting agents for their ability to prevent the activation of cell growth and proliferation signals. Card...

Air quality monitoring using mobile microscopy and machine learning.

Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. I...

Assessment of the water quality monitoring network of the Piabanha River experimental watersheds in Rio de Janeiro, Brazil, using autoassociative neural networks.

Water quality monitoring is a complex issue that requires support tools in order to provide information for water resource management. Budget constrai...

Improving the Quality of Positive Datasets for the Establishment of Machine Learning Models for pre-microRNA Detection.

MicroRNAs (miRNAs) are involved in the post-transcriptional regulation of protein abundance and thus have a great impact on the resulting phenotype. I...

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks.

Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for pati...

DrugSemantics: A corpus for Named Entity Recognition in Spanish Summaries of Product Characteristics.

For the healthcare sector, it is critical to exploit the vast amount of textual health-related information. Nevertheless, healthcare providers have di...

A deep learning approach for predicting the quality of online health expert question-answering services.

Recently, online health expert question-answering (HQA) services (systems) have attracted more and more health consumers to ask health-related questio...

Automated Spirometry Quality Assurance: Supervised Learning From Multiple Experts.

Forced spirometry testing is gradually becoming available across different healthcare tiers including primary care. It has been demonstrated in earlie...