Information Technology

HybridTrust: on-device federated learning with crypto-agile security for legacy and quantum-safe medical devices.

The process of migration of IoMT systems in healthcare into post-quantum cryptographic systems is expected to be a gradual one. Here, existing ECC-based devices alongside newly developed quantum-resistant devices will be operating within the same healthcare ecosystem. However, there exists an important interoperability challenge posed by the need for collaboration within the domain of edge intelli...

Predicting type II diabetes mellitus in young and middle-aged adults: A machine learning approach using the Utah population database.

AIMS: To develop a machine learning framework for predicting type 2 diabetes mellitus (T2DM) using administrative data and electronic health records (EHR) that could be applied in healthcare settings. METHODS: Study population included parents of individuals born in 1970-1990 who resided in Utah urban counties during 1990-2015. Two prediction models were developed using classification and regressi...

Development of Machine Learning Models to Predict Candidemia in Hospitalized Adult Patients.

PURPOSE: We aimed to develop a generalizable machine learning model that leverages electronic medical record (EMR) data to predict candidemia using in...

Standardization of surgical gesture taxonomy: a SAGES Delphi consensus study.

INTRODUCTION: Artificial intelligence (AI) for surgical workflow analysis often fails to generalize because surgical actions lack a standardized, fine...

Comparison of machine learning methods for prediction of venous thromboembolism among hospitalized adults.

BACKGROUND: Hospital-acquired venous thromboembolism (HA-VTE) is a significant cause of morbidity and mortality among hospitalized adults. Accurate pr...

Artificial intelligence and advanced monitoring for air and water pollution control in the USA: opportunities, challenges, and policy directions.

In this review article, we present the current state of artificial intelligence and advanced technologies in air and water pollution monitoring in the...

Maturity, Safety, and Equity of AI-Enabled Systems and Triage in Integrated Primary Care.

Artificial intelligence (AI)-enabled systems must simultaneously improve the Quintuple Aim and digital health maturity, including equitable access to ...

Multimodal Fusion of Echocardiogram Images and Electronic Medical Records for Heart Disease Screening: Retrospective Algorithm Development and Validation Study.

BACKGROUND: Echocardiography is a fundamental imaging modality for the diagnosis of heart disease (HD), but its interpretation remains operator-depend...

Randomized trial of electronic health record implemented AI risk prediction in kidney transplant care.

Artificial intelligence (AI)-based risk prediction is increasingly implemented in clinical care, but randomized evidence on communication and shared d...

In-depth serum proteomics atlas of COVID-19 defines a Severity-Resistance Index from a four-protein panel for disease severity and prognosis.

BACKGROUND: COVID-19 exhibits seasonal epidemics with high risk of mortality in vulnerable population. Identifying accurate parameters for predicting ...

Transforming Pediatric Care Through AI: Bridging the Digital Divide in Health Informatics.

Health informatics and artificial intelligence (AI) technologies are increasingly influencing pediatric health care delivery across diverse health sys...

Developing and validating an electronic health record-embedded AI model for managing multimorbid hospitalisation risk in patients with chronic RESpiratory disease (AiRES): a study protocol.

BACKGROUND: Chronic respiratory diseases (CRDs), such as asthma and chronic obstructive pulmonary disease (COPD), are heterogeneous conditions with a ...

A lifecycle governance and learning health system framework for trustworthy, generalizable, and sustainable human-ai partnership in clinical practice: Lessons from the asthma-guidance and prediction system (A-GPS).

The integration of artificial intelligence (AI) into clinical decision support (CDS) holds promise for proactive, personalized, and precision care. Ho...

Development and validation of a deep learning model for liver shear stiffness regression using abdominal multiparametric MRI across multiple sites and vendors.

OBJECTIVE: Liver stiffness measurement is important for assessing chronic liver disease (CLD). MR elastography (MRE) requires specialized hardware and...

Digital twin-centered food safety management systems: A review of IoT, AI, and blockchain integration for bacterial pathogen control.

The digitalization of food safety management systems (FSMS) represents a crucial strategy for mitigating persistent pathogen contamination and foodbor...

Diagnostic stewardship monitoring systems: institutional and system-level approaches.

Diagnostic stewardship-performing the right test for the right patient at the right time-improves diagnostic accuracy and reduces healthcare resource ...

Addressing the Treatment Gap for Pediatric Headache in Underserved Regions.

PURPOSE OF REVIEW: This review explores innovative strategies to address the treatment gap for pediatric headache disorders in underserved regions wor...

Big data and artificial intelligence in animal nutrition: a new era of precision feeding.

The convergence of Big Data and Artificial Intelligence (AI) is redefining animal nutrition by enabling precision feeding systems that are individuali...

Multi-modal personalized federated learning with adaptive differential privacy for medical image classification and a privacy-preserving approach.

Deep learning on medical images classification intervention needs to use large data on multi-institutional datasets but privacy laws inhibit sharing o...

Comparing machine and deep learning models for pediatric anxiety classification using structured EHRs and area-based measures of health data.

OBJECTIVE: This retrospective, case-control study with internal validation evaluates the performance of machine learning (ML) and deep learning (DL) m...