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Information Technology

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

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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 pre...

A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms.

Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascula...

Intelligent Techniques for Detecting Network Attacks: Review and Research Directions.

The significant growth in the use of the Internet and the rapid development of network technologies ...

Estimating redundancy in clinical text.

The current mode of use of Electronic Health Records (EHR) elicits text redundancy. Clinicians often...

Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment.

PURPOSE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness related to oxyge...

Enabling Security Services in Socially Assistive Robot Scenarios for Healthcare Applications.

Today's IoT deployments are highly complex, heterogeneous and constantly changing. This poses severe...

An empirical study of using radiology reports and images to improve ICU-mortality prediction.

The predictive Intensive Care Unit (ICU) scoring system plays an important role in ICU management fo...

Explainable Molecular Sets: Using Information Theory to Generate Meaningful Descriptions of Groups of Molecules.

Algorithmically identifying the meaningful similarities between an assortment of molecules is a crit...

Machine learning and artificial intelligence: applications in healthcare epidemiology.

Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated wi...

Automation of penicillin adverse drug reaction categorisation and risk stratification with machine learning natural language processing.

BACKGROUND: The penicillin adverse drug reaction (ADR) label is common in electronic health records ...

Natural Language Mapping of Electrocardiogram Interpretations to a Standardized Ontology.

BACKGROUND: Interpretations of the electrocardiogram (ECG) are often prepared using software outside...

The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning Applications.

With vast interest in machine learning applications, more investigators are proposing to assemble la...

Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients.

The combination of machine learning (ML) and electronic health records (EHR) data may be able to imp...

Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling.

Many individuals visit rural telemedicine centres to obtain safe and effective health remedies for t...

Subcategorizing EHR diagnosis codes to improve clinical application of machine learning models.

BACKGROUND: Electronic health record (EHR) data is commonly used for secondary purposes such as rese...

Federated learning for predicting clinical outcomes in patients with COVID-19.

Federated learning (FL) is a method used for training artificial intelligence models with data from ...

[Digitization of the healthcare system: the BfArM's contribution to the development of potential].

Digitalization is a clear megatrend of our time, also in the health sector, which is currently exper...

A Few-Shot Learning-Based Siamese Capsule Network for Intrusion Detection with Imbalanced Training Data.

Network intrusion detection remains one of the major challenges in cybersecurity. In recent years, m...

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread an...

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