Information Technology

A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models.

Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially comparative effectiveness studies, failure to adjust for SBDoH factors will potentially cause confounding issues and misclassification errors in either statistical analyses and machine learning-based models. However, there are limited studies to examine SBD...

Mixed-methods evaluation of three natural language processing modeling approaches for measuring documented goals-of-care discussions in the electronic health record.

CONTEXT: Documented goals-of-care discussions are an important quality metric for patients with serious illness. Natural language processing (NLP) is a promising approach for identifying goals-of-care discussions in the electronic health record (EHR).

3DMesh-GAR: 3D Human Body Mesh-Based Method for Group Activity Recognition.

Group activity recognition is a prime research topic in video understanding and has many practical applications, such as crowd behavior monitoring, vi...

Digital Health Policy and Programs for Hospital Care in Vietnam: Scoping Review.

BACKGROUND: There are a host of emergent technologies with the potential to improve hospital care in low- and middle-income countries such as Vietnam....

Fusion of sequential visits and medical ontology for mortality prediction.

The goal of mortality prediction task is to predict the future death risk of patients according to their previous Electronic Healthcare Records (EHR)....

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology.

Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management an...

Classification and Explanation for Intrusion Detection System Based on Ensemble Trees and SHAP Method.

In recent years, many methods for intrusion detection systems (IDS) have been designed and developed in the research community, which have achieved a ...

Evaluation of Machine Learning Techniques to Predict the Likelihood of Mental Health Conditions Following a First mTBI.

OBJECTIVE: Limited research has evaluated the utility of machine learning models and longitudinal data from electronic health records (EHR) to forecas...

Machine learning and artificial intelligence in research and healthcare.

Artificial intelligence (AI) is a broad term referring to the application of computational algorithms that can analyze large data sets to classify, pr...

Assessment of Smartphone-Based Spiral Tracing in Multiple Sclerosis Reveals Intra-Individual Reproducibility as a Major Determinant of the Clinical Utility of the Digital Test.

Technological advances, lack of medical professionals, high cost of face-to-face encounters, and disasters such as the COVID-19 pandemic fuel the tele...

Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification.

BACKGROUND: Electronic health records (EHRs) are a rich source of longitudinal patient data. However, missing information due to clinical care that pr...

Analysis of Clinical Parameters, Drug Consumption and Use of Health Resources in a Southern European Population with Alcohol Abuse Disorder during COVID-19 Pandemic.

The disruption in healthcare attention to people with alcohol dependence, along with psychological decompensation as a consequence of lockdown derived...

Explainable deep learning in healthcare: A methodological survey from an attribution view.

The increasing availability of large collections of electronic health record (EHR) data and unprecedented technical advances in deep learning (DL) hav...

Application of deterministic networking for reducing network delay in urological telesurgery: A retrospective study.

BACKGROUND: Deterministic Networking (DetNet) is a new technology that can effectively control network delay and may promote the revolution of telemed...

An explainable machine learning framework for lung cancer hospital length of stay prediction.

This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed t...

A Hybrid Framework for Intrusion Detection in Healthcare Systems Using Deep Learning.

The unbounded increase in network traffic and user data has made it difficult for network intrusion detection systems to be abreast and perform well. ...

Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing.

OBJECTIVE: Social determinants of health (SDOH) are non-medical factors that can profoundly impact patient health outcomes. However, SDOH are rarely a...

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients.

Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of...

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

Rapid technological development has changed drastically the automotive industry. Network communication has improved, helping the vehicles transition f...

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 target preventative resources toward high-risk pa...