Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Primary care presents an ideal opportunity for early detection of cognitive impairment, yet primary care clinics face barriers to cognitive screening. MyCog, an EHR-integrated tablet app that is self-administered during the rooming process of a primary care visit, streamlines the screening process to reduce barriers and encourage broader screening. We compared MyCog performance from 65 adults with...
The integration of intelligent technologies in operating room nursing represents a rapidly evolving field requiring systematic analysis to understand global research trends and development patterns. This study aimed to comprehensively analyze worldwide research trends, identify key contributors, and reveal emerging developments in intelligent operating room nursing through bibliometric analysis. A...
Conducting a systematic review is labour-intensive and time-consuming, especially during the study screening process. Previous research has introduced...
This study addresses the critical implementation science challenge of operationalizing social determinants of health (SDoH) in clinical practice. We d...
Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection is essential for improving survival through timel...
Early detection of cognitive impairment in assisted living is hindered by time-intensive tools like MMSE and MoCA. We present a 60-second voice-based ...
Chatbots have the potential to reduce barriers to pre-exposure prophylaxis (PrEP), including lack of awareness, misconceptions, and stigma, by providi...
Advancements in imaging technology, alongside increasing longevity and co-morbidities, have led to heightened demand for diagnostic radiology services...
To compare the performance of a foundation model and a supervised learning-based model for detecting referable glaucoma from fundus photographs. Evalu...
This study aimed to optimise the balance between participant burden and performance of algorithms predicting high-risk moments for a smoking cessation...
Sepsis remains a leading cause of mortality in intensive care units (ICUs) worldwide, underscoring the urgent need for early detection to improve pati...
This narrative review examines the theoretical foundations of mental workload, evaluates biometric monitoring methods, addresses ethical and privacy i...
Diabetes-related foot ulcers (DFUs) are a serious complication of diabetes, often resulting in infection, amputation, or even mortality. Offloading fo...
Artificial intelligence (AI) and statistical models designed to predict same-admission outcomes for hospitalized patients, such inpatient mortality, o...
Client attendance is vital for the success of HIV vertical transmission prevention programs, yet 23.4% of clients missed follow-up appointments after ...
Although there are numerous studies exploring predictors of clinical trial failure, there is a lack of structured knowledge of the methodological nuan...
Progressive supranuclear palsy (PSP) is typically characterized by vertical supranuclear gaze palsy and early falls, referred to as Richardson’s syndr...
Recovery from aphasia after stroke is thought to depend on functional reorganization of language processing in surviving brain regions. Many studies h...
To evaluate convolutional neural network (CNN) model training strategies that optimize the performance of calcaneus fracture detection on radiographs ...
To develop privacy-enhancing statistical methods for estimation of binary disease risk model association parameters across multiple electronic health ...