Information Technology

Safe medicine recommendation via star interactive enhanced-based transformer model.

With the rapid development of electronic medical records (EMRs), most existing medicine recommendation systems based on EMRs explore knowledge from the diagnosis history to help doctors prescribe medication correctly. However, due to the limitations of the EMRs' content, recommendation systems cannot explicitly reflect relevant medical data, such as drug interactions. In recent years, medicine rec...

Registries, Databases and Repositories for Developing Artificial Intelligence in Cancer Care.

Modern artificial intelligence techniques have solved some previously intractable problems and produced impressive results in selected medical domains. One of their drawbacks is that they often need very large amounts of data. Pre-existing datasets in the form of national cancer registries, image/genetic depositories and clinical datasets already exist and have been used for research. In theory, t...

Development of an IoT Architecture Based on a Deep Neural Network against Cyber Attacks for Automated Guided Vehicles.

This paper introduces an integrated IoT architecture to handle the problem of cyber attacks based on a developed deep neural network (DNN) with a rect...

Temporal Weighted Averaging for Asynchronous Federated Intrusion Detection Systems.

Federated learning (FL) is an emerging subdomain of machine learning (ML) in a distributed and heterogeneous setup. It provides efficient training arc...

Fusion Models for Generalized Classification of Multi-Axial Human Movement: Validation in Sport Performance.

We introduce a set of input models for fusing information from ensembles of wearable sensors supporting human performance and telemedicine. Veracity i...

Identifying and evaluating clinical subtypes of Alzheimer's disease in care electronic health records using unsupervised machine learning.

BACKGROUND: Alzheimer's disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Unders...

A weakly supervised model for the automated detection of adverse events using clinical notes.

With clinical trials unable to detect all potential adverse reactions to drugs and medical devices prior to their release into the market, accurate po...

AI in predicting COPD in the Canadian population.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that produces non-reversible airflow limitations. Approximately 10% of Cana...

DI++: A deep learning system for patient condition identification in clinical notes.

Accurately recording a patient's medical conditions in an EHR system is the basis of effectively documenting patient health status, coding for billing...

Telemedical percussion: objectifying a fundamental clinical examination technique for telemedicine.

PURPOSE: While demand for telemedicine is increasing, patients are currently restricted to tele-consultation for the most part. Fundamental diagnostic...

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions.

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mech...

Natural language processing of head CT reports to identify intracranial mass effect: CTIME algorithm.

BACKGROUND: The Mortality Probability Model (MPM) is used in research and quality improvement to adjust for severity of illness and can also inform tr...

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is ...

Linking Free Text Documentation of Functioning and Disability to the ICF With Natural Language Processing.

BACKGROUND: Invaluable information on patient functioning and the complex interactions that define it is recorded in free text portions of the Electro...

Interpretable time-aware and co-occurrence-aware network for medical prediction.

BACKGROUND: Disease prediction based on electronic health records (EHRs) is essential for personalized healthcare. But it's hard due to the special da...

Prediction-Correction Techniques to Support Sensor Interoperability in Industry 4.0 Systems.

Industry 4.0 is envisioned to transform the entire economical ecosystem by the inclusion of new paradigms, such as cyber-physical systems or artificia...

Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records.

IMPORTANCE: Detecting cognitive decline earlier among older adults can facilitate enrollment in clinical trials and early interventions. Clinical note...

Novelelectronic health records applied for prediction of pre-eclampsia: Machine-learning algorithms.

OBJECTIVE: To predict risk of pre-eclampsia (PE) in women using machine learning (ML) algorithms, based on electronic health records (EHR) collected a...

Robotic endovascular surgery: current and future practice.

Minimally invasive techniques have been at the forefront of surgical progress, and the evolution of endovascular robotic technologies has seen a parad...

Complete Molar Pregnancies with a Coexisting Fetus: Pregnancy Outcomes and Review of Literature.

 The objective of the study was to review the obstetric outcomes of complete hydatidiform molar pregnancies with a coexisting fetus (CHMCF), a rare c...