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Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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Attacks to Automatous Vehicles: A Deep Learning Algorithm for Cybersecurity.

Rapid technological development has changed drastically the automotive industry. Network communicati...

Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to...

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

With the rapid development of electronic medical records (EMRs), most existing medicine recommendati...

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

Modern artificial intelligence techniques have solved some previously intractable problems and produ...

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...

Temporal Weighted Averaging for Asynchronous Federated Intrusion Detection Systems.

Federated learning (FL) is an emerging subdomain of machine learning (ML) in a distributed and heter...

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 support...

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...

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 p...

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 doc...

AI in predicting COPD in the Canadian population.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that produces non-reversi...

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

PURPOSE: While demand for telemedicine is increasing, patients are currently restricted to tele-cons...

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 adj...

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...

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 i...

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 para...

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

BACKGROUND: Disease prediction based on electronic health records (EHRs) is essential for personaliz...

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 clin...

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, ba...

Robotic endovascular surgery: current and future practice.

Minimally invasive techniques have been at the forefront of surgical progress, and the evolution of ...

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