Information Technology

Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review.

Electronic health records (EHR) have revolutionized cardiovascular disease (CVD) research by enabling comprehensive, large-scale, and dynamic data collection. Integrating EHR data with advanced analytical methods, including artificial intelligence (AI), transforms CVD risk prediction and management methodologies. This review examines the advancements and challenges of using EHR in developing CVD p...

Toward a conceptual model to improve the user experience of a sustainable and secure intelligent transport system.

The rapid advancement of automotive technologies has spurred the development of innovative applications within intelligent transportation systems (ITS), aimed at enhancing safety, efficiency and sustainability. These applications, such as advanced driver assistance systems (ADAS), vehicle-to-everything (V2X) communication and autonomous driving, are transforming transportation by enabling adaptive...

Harmonizing foundation models in healthcare: A comprehensive survey of their roles, relationships, and impact in artificial intelligence's advancing terrain.

The lightning development of artificial intelligence (AI) has revolutionized healthcare, helping significant improvements in various applications. Thi...

Application of the LDA model to identify topics in telemedicine conversations on the X social network.

The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obligatory use of digital media in many sectors, as is t...

Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.

AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical met...

Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.

OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using se...

Joint fusion of EHR and ECG data using attention-based CNN and ViT for predicting adverse clinical endpoints in percutaneous coronary intervention patients.

Predicting post-Percutaneous Coronary Intervention (PCI) outcomes is crucial for effective patient management and quality improvement in healthcare. H...

Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.

OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP)...

Enhancing diagnosis prediction with adaptive disease representation learning.

Diagnosis prediction predicts which diseases a patient is most likely to suffer from in the future based on their historical electronic health records...

Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges.

This paper presents a comprehensive systematic review of generative models (GANs, VAEs, DMs, and LLMs) used to synthesize various medical data types, ...

Artificial intelligence in public health: promises, challenges, and an agenda for policy makers and public health institutions.

Artificial intelligence (AI) can rapidly analyse large and complex datasets, extract tailored recommendations, support decision making, and improve th...

Prediction and detection of terminal diseases using Internet of Medical Things: A review.

The integration of Artificial Intelligence (AI) with the Internet of Medical Things (IoMT) has revolutionized disease prediction and detection, but ch...

CECRel: A joint entity and relation extraction model for Chinese electronic medical records of coronary angiography via contrastive learning.

Entity and relation extraction from Chinese electronic medical records (EMRs) is a crucial foundation for constructing medical knowledge graphs and su...

Cognitive performance classification of older patients using machine learning and electronic medical records.

Dementia rates are projected to increase significantly by 2050, posing considerable challenges for healthcare systems worldwide. Developing efficient ...

Hyperfusion: A hypernetwork approach to multimodal integration of tabular and medical imaging data for predictive modeling.

The integration of diverse clinical modalities such as medical imaging and the tabular data extracted from patients' Electronic Health Records (EHRs) ...

An effective multi-step feature selection framework for clinical outcome prediction using electronic medical records.

BACKGROUND: Identifying key variables is essential for developing clinical outcome prediction models based on high-dimensional electronic medical reco...

Prediction of 90 day mortality in elderly patients with acute HF from e-health records using artificial intelligence.

AIMS: Mortality risk after hospitalization for heart failure (HF) is high, especially in the first 90 days. This study aimed to construct a model auto...

Natural language processing techniques applied to the electronic health record in clinical research and practice - an introduction to methodologies.

Natural Language Processing (NLP) has the potential to revolutionise clinical research utilising Electronic Health Records (EHR) through the automated...

RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS).

Acute respiratory distress syndrome (ARDS) is a severe organ dysfunction associated with significant mortality and morbidity among critically ill pati...

An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets.

Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This ...