Latest AI and machine learning research in medicare for healthcare professionals.
Biological inspiration offers new and innovative solutions to exploring challenging terrains, and implementations in bio-inspired robotics in turn offers insights to biological form and function. In particular, annelids (segmented worms), such asNereissp. (bristleworms), are useful subjects for their multi-modal locomotion through differing environments. This research aims to mimic key anatomical ...
BACKGROUND: Screening for atrial fibrillation (AF) may lead to earlier detection and initiation of preventive measures. Current AF screening approaches using a guideline age-based threshold of ≥65 years have shown limited yield. OBJECTIVES: In an AF screening trial, we assessed whether the screening effect was larger among individuals at elevated AF risk using validated clinical and electrocardiog...
Computational in silico methods offer a powerful alternative to animal-based toxicity testing, which remains time-consuming, expensive, and ethically ...
BACKGROUND: Knowledge-based planning (KBP) tools rely on large datasets of clinical plans, which are often difficult to collect, particularly in new o...
Machine learning (ML) surrogate models are increasingly employed to accelerate materials discovery, yet their transferability across heterogeneous dat...
BACKGROUND: Clinical trial enrollment in oncology remains critically low, with fewer than 5% of eligible adults participating, in large part due to th...
Medical education has long relied on stable, high-level program objectives to articulate the outcomes of undergraduate medical training. These objecti...
BACKGROUND: Virtual monoenergetic imaging (VMI) at 40 keV improves iodine attenuation in colon cancer CT but is constrained by severe image noise. Dee...
The complementarity-determining regions (CDRs) of antibodies are loop structures that are key to their interactions with antigens and are of high impo...
Health care professionals face an urgent need for AI literacy as artificial intelligence technologies rapidly transform clinical practice, yet nursing...
PURPOSE: To develop and validate a protocol-agnostic machine learning platform ("Predictive Planning") for knowledge-based planning (KBP) in external ...
OBJECTIVE: The 2025 measles outbreak in Mexico (5741 cases) marked a severe decline in immunization resilience. We aimed to measure this systemic vuln...
PURPOSE: Exosome-surface enhanced Raman spectroscopy-artificial intelligence platform (exosome-SERS-AI) is an innovative liquid biopsy method that acq...
BACKGROUND: Improving screening coverage is a central goal of the global strategy to eliminate cervical cancer. In resource-constrained settings, insu...
BACKGROUND: As the global population continues to age, the prevalence of geriatric conditions, including dementia and frailty, is also increasing. Ear...
OBJECTIVE: To develop a machine learning (ML) algorithm that improves accuracy compared to the Hierarchical Condition Category (HCC) score used by the...
The game changers in mental health and substance use disorder treatment have been shaped by historical sea changes marked by transformative advancemen...
Coal combustion emissions significantly contribute to air pollution in China, especially in the residential sector, where they are widely dispersed an...
BACKGROUND: Smartphones generate continuous behavioral signals such as mobility and activity patterns, offering scalable opportunities for monitoring ...
BACKGROUND: Neglected Tropical Diseases (NTDs) affect 1.5 billion people worldwide with 39% of the global burden occurring in Africa. In Kenya, NTDs r...