Information Technology

Artificial intelligence-assisted automated heart failure detection and classification from electronic health records.

AIMS: Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. We hypothesized that by applying keyword searches to routinely stored EHR, in conjunction with AI-powered automated reading of DICOM echocardiography ...

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approach. We retrospectively gathered medical data from 13 440 pediatric patients slated for surgery from 2018 to 2021. Following data preprocessing, we uti...

A Scoping Review of Studies Using Artificial Intelligence Identifying Optimal Practice Patterns for Inpatients With Type 2 Diabetes That Lead to Positive Healthcare Outcomes.

The objective of this scoping review was to survey the literature on the use of AI/ML applications in analyzing inpatient EHR data to identify bundles...

Enhancing Healthcare through Sensor-Enabled Digital Twins in Smart Environments: A Comprehensive Analysis.

This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within s...

[Data-driven intensive care: a lack of comprehensive datasets].

Intensive care units provide a data-rich environment with the potential to generate datasets in the realm of big data, which could be utilized to trai...

Redefining Healthcare With Artificial Intelligence (AI): The Contributions of ChatGPT, Gemini, and Co-pilot.

Artificial Intelligence (AI) in healthcare marks a new era of innovation and efficiency, characterized by the emergence of sophisticated language mode...

Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records.

Observational causal inference is useful for decision-making in medicine when randomized clinical trials (RCTs) are infeasible or nongeneralizable. Ho...

Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.

BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in me...

Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.

BACKGROUND: Referral of patients with heart failure (HF) who are at high mortality risk for specialist evaluation is recommended. Yet, most tools for ...

[Orthopedics and trauma surgery in the digital age].

BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedicine, digital health applications, electronic pati...

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, su...

Artificial Intelligence in Hand Surgery - How Generative AI is Transforming the Hand Surgery Landscape.

Artificial intelligence (AI) has witnessed significant advancements, reshaping various industries, including healthcare. The introduction of ChatGPT b...

Diagnosing glaucoma in primary eye care and the role of Artificial Intelligence applications for reducing the prevalence of undetected glaucoma in Australia.

Glaucoma is the commonest cause of irreversible blindness worldwide, with over 70% of people affected remaining undiagnosed. Early detection is crucia...

Applying Object Detection and Large Language Model to Establish a Smart Telemedicine Diagnosis System with Chatbot: A Case Study of Pressure Injuries Diagnosis System.

The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical exam...

Novel Technologies in Artificial Intelligence and Telemedicine for Glaucoma Screening.

PURPOSE: To provide an overview of novel technologies in telemedicine and artificial intelligence (AI) approaches for cost-effective glaucoma screenin...

De-identification of clinical free text using natural language processing: A systematic review of current approaches.

BACKGROUND: Electronic health records (EHRs) are a valuable resource for data-driven medical research. However, the presence of protected health infor...

A machine learning approach for diagnostic and prognostic predictions, key risk factors and interactions.

Machine learning (ML) has the potential to revolutionize healthcare, allowing healthcare providers to improve patient-care planning, resource planning...

Q-learning and fuzzy logic multi-tier multi-access edge clustering for 5g v2x communication.

The 5th generation (5 G) network is required to meet the growing demand for fast data speeds and the expanding number of customers. Apart from offerin...

[Analysis of the challenges and dilemmas that bioethics of the 21st century will face in the digital health era].

The medical history underscores the significance of ethics in each advancement, with bioethics playing a pivotal role in addressing emerging ethical c...

Deep learning model for personalized prediction of positive MRSA culture using time-series electronic health records.

Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA...