Latest AI and machine learning research in information technology for healthcare professionals.
This study aimed to develop and validate a transformer-based early warning score (TEWS) system for predicting adverse events (AEs) in the emergency department (ED). We conducted a retrospective study analyzing adult ED visits at a tertiary hospital. The TEWS was developed to predict five AEs within 24Â h: vasopressor use, respiratory support, intensive care unit admission, septic shock, and cardiac...
The rapid growth of medical imaging data presents challenges for efficient storage and transmission, particularly in clinical and telemedicine applications where image fidelity is crucial. This study proposes a hybrid deep learning-based image compression framework that integrates Stationary Wavelet Transform (SWT), Stacked Denoising Autoencoder (SDAE), Gray-Level Co-occurrence Matrix (GLCM), and ...
High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screen...
Arthritis is a complex group of disorders characterized by inflammation of the joints and poses a significant burden on global health. The most preval...
The rapid expansion of Internet of Things (IoT) networks necessitates efficient intrusion detection systems (IDS) capable of operating within the stri...
The rapid adoption of Internet of Things (IoT) devices has significantly increased cybersecurity risks, making them vulnerable to anomalies, attacks, ...
The emergence of large language models (LLMs) opens new horizons to leverage, often unused, information in clinical text. Our study aims to capitalise...
This study delves into the vulnerability of the smart grid to infiltration by hackers and proposes methods to safeguard it by leveraging blockchain an...
The role of electric vehicles (EV) is crucial in the shift toward sustainable transportation while reducing greenhouse gas emissions. However, integra...
The Internet of Medical Things (IoMT) has transformed healthcare delivery but faces critical challenges, including cybersecurity threats that endanger...
Growing volumes and sensitivities of information in the growing IoT require strong cybersecurity measures to adequately counter increasingly sophistic...
Occupational data is a crucial social determinant of health, influencing diagnostic accuracy, treatment strategies, and policy-making in healthcare. H...
Risk adjustment is a critical component of health care reimbursement aimed at ensuring fair compensation on the basis of the characteristics of patien...
BACKGROUND: Acute kidney injury (AKI) and acute kidney disease (AKD) are frequent complications of hospitalization, resulting in reduced outcomes and ...
Electronic health record (EHR)-based models to identify individuals who may benefit from pre-exposure prophylaxis (PrEP) outperform traditional risk s...
BACKGROUND: With the increasing prevalence of patients on home mechanical ventilation (HMV), changing indications, shortage of hospital resources, and...
Blockchain technology (BCT) enables the building of a distributed decentralized network that securely stores and exchanges unchangeable data, controll...
In recent years, the medical field has seen significant advancements in the field of robotics and artificial intelligence (AI). However, many healthca...
The integration of wearable medical devices into surgical practice has transformed the field, enabling enhanced precision, informed decision-making, a...
BACKGROUND: Early sepsis diagnosis is essential for initiating prompt treatment, preventing the progression of organ failure, and improving the surviv...