Information Technology

Benchmarking Transformer-Based Models for Identifying Social Determinants of Health in Clinical Notes.

Electronic health records (EHR) have been widely used in building machine learning models for health outcomes prediction. However, many EHR-based models are inherently biased due to lack of risk factors on social determinants of health (SDoH), which are responsible for up to 40% preventive deaths. As SDoH information is often captured in clinical notes, recent efforts have been made to extract suc...

Economic and Environmental Costs of Cloud Technologies for Medical Imaging and Radiology Artificial Intelligence.

Radiology is on the verge of a technological revolution driven by artificial intelligence (including large language models), which requires robust computing and storage capabilities, often beyond the capacity of current non-cloud-based informatics systems. The cloud presents a potential solution for radiology, and we should weigh its economic and environmental implications. Recently, cloud technol...

Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.

PURPOSE: Advances in artificial intelligence have enabled the development of predictive models for glaucoma. However, most work is single-center and u...

Novel Preoperative Risk Stratification Using Digital Phenotyping Applying a Scalable Machine-Learning Approach.

BACKGROUND: Classification of perioperative risk is important for patient care, resource allocation, and guiding shared decision-making. Using discrim...

Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases.

INTRODUCTION: Healthcare data and the knowledge gleaned from it play a key role in improving the health of current and future patients. These knowledg...

Skin Inclusion: Addressing Deficits in Medical Education to Promote Diversity in Dermatological Diagnosis and Treatment.

Dermatological conditions impact many people globally, including those with melanin-rich skin. However, insufficient medical education contributes to ...

Digital solutions and health sciences.

Digitalization is the conversion of analog data and information to a digital format based on bits. Digitalization allows information to be managed in ...

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach.

Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known li...

Informed consent for artificial intelligence in emergency medicine: A practical guide.

As artificial intelligence (AI) expands its presence in healthcare, particularly within emergency medicine (EM), there is growing urgency to explore t...

Using an artificial intelligence tool incorporating natural language processing to identify patients with a diagnosis of ANCA-associated vasculitis in electronic health records.

BACKGROUND: Because anti-neutrophil cytoplasmatic antibody (ANCA)-associated vasculitis (AAV) is a rare, life-threatening, auto-immune disease, conduc...

Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.

This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote monitoring through the development of a real-time wh...

A Chinese telemedicine-dialogue dataset annotated for named entities.

BACKGROUND: A large collection of dialogues between patients and doctors must be annotated for medical named entities to build intelligence for teleme...

Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.

Delirium is a syndrome of acute brain failure which is prevalent amongst older adults in the Intensive Care Unit (ICU). Incidence of delirium can sign...

A Deep Learning Approach for Automatic and Objective Grading of the Motor Impairment Severity in Parkinson's Disease for Use in Tele-Assessments.

Wearable sensors provide a tool for at-home monitoring of motor impairment progression in neurological conditions such as Parkinson's disease (PD). Th...

Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care.

It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support indep...

Feasibility and Safety of 5G-Based Telerobotic Abdominal Ultrasonography.

OBJECTIVE: Telemedicine can offer services to remote patients regardless of the distance. Fifth-generation (5G) mobile networks may make telemedicine ...

Artificial Intelligence and Postoperative Monitoring in Plastic Surgery.

Technological innovation has fueled an evolving landscape in plastic surgery. Recently, artificial intelligence (AI) has demonstrated tremendous poten...

Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions.

Hospitals use medical cyber-physical systems (MCPS) more often to give patients quality continuous care. MCPS isa life-critical, context-aware, networ...

Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions.

Acute kidney injury (AKI) has a significant impact on the short-term and long-term clinical outcomes of pediatric and neonatal patients, and it is imp...

Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era.

Recently, fundus photography (FP) is being increasingly used. Corneal curvature is an essential factor in refractive errors and is associated with sev...