Information Technology

Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection.

Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is the diagnosis method recommended by the World Health Organization (WHO) although it often presents a decreased sensitivity in low transmission settings and it is labour intensive. Visual reading of Kato-Katz preparations requires the samples to be anal...

Applying interpretable deep learning models to identify chronic cough patients using EHR data.

BACKGROUND AND OBJECTIVE: Chronic cough (CC) affects approximately 10% of adults. Many disease states are associated with chronic cough, such as asthma, upper airway cough syndrome, bronchitis, and gastroesophageal reflux disease. The lack of an ICD code specific for chronic cough makes it challenging to identify such patients from electronic health records (EHRs). For clinical and research purpos...

A Review of Recent Work in Transfer Learning and Domain Adaptation for Natural Language Processing of Electronic Health Records.

OBJECTIVES: We survey recent work in biomedical NLP on building more adaptable or generalizable models, with a focus on work dealing with electronic h...

Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction.

Electronic health records (EHRs) are characterized as nonstationary, heterogeneous, noisy, and sparse data; therefore, it is challenging to learn the ...

Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management.

The study aims to explore the application of international classification of diseases (ICD) coding technology and embedded electronic medical record (...

Robotics for neuroendovascular intervention: Background and primer.

The simultaneous growth of robotic-assisted surgery and telemedicine in recent years has only been accelerated by the recent coronavirus disease 2019 ...

Platform for Healthcare Promotion and Cardiovascular Disease Prevention.

This article presents the hardware-software design and implementation of an open, integrated, and scalable healthcare platform oriented to multiple po...

EHR-Oriented Knowledge Graph System: Toward Efficient Utilization of Non-Used Information Buried in Routine Clinical Practice.

Non-used clinical information has negative implications on healthcare quality. Clinicians pay priority attention to clinical information relevant to t...

Prediction Model Using Machine Learning for Mortality in Patients with Heart Failure.

Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US population, the public health burden of HF is enormous....

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of electronic health records (EHRs) offers a unique oppo...

Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.

IMPORTANCE: Electronic health records (EHRs) provide a low-cost means of accessing detailed longitudinal clinical data for large populations. A lung c...

Using NLP in openEHR archetypes retrieval to promote interoperability: a feasibility study in China.

BACKGROUND: With the development and application of medical information system, semantic interoperability is essential for accurate and advanced healt...

The Proposition and Evaluation of the RoEduNet-SIMARGL2021 Network Intrusion Detection Dataset.

Cybersecurity is an arms race, with both the security and the adversaries attempting to outsmart one another, coming up with new attacks, new ways to ...

Towards Semantic Integration of Machine Vision Systems to Aid Manufacturing Event Understanding.

A manufacturing paradigm shift from conventional control pyramids to decentralized, service-oriented, and cyber-physical systems (CPSs) is taking plac...

An Improved Vulnerability Exploitation Prediction Model with Novel Cost Function and Custom Trained Word Vector Embedding.

Successful cyber-attacks are caused by the exploitation of some vulnerabilities in the software and/or hardware that exist in systems deployed in prem...

Treatment initiation prediction by EHR mapped PPD tensor based convolutional neural networks boosting algorithm.

Electronic health records contain patient's information that can be used for health analytics tasks such as disease detection, disease progression pre...

Improving the Performance of Machine Learning-Based Network Intrusion Detection Systems on the UNSW-NB15 Dataset.

Networks are exposed to an increasing number of cyberattacks due to their vulnerabilities. So, cybersecurity strives to make networks as safe as possi...

Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population.

PURPOSE: The depth and breadth of clinical data within electronic health record (EHR) systems paired with innovative machine learning methods can be l...

Prediction of Bedridden Duration of Hospitalized Patients by Machine Learning Based on EMRs at Admission.

Being bedridden is a frequent comorbid condition that leads to a series of complications in clinical practice. The present study aimed to predict bedr...

Improvements to PTSD quality metrics with natural language processing.

RATIONALE AIMS AND OBJECTIVES: As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) d...