Artificial Intelligence Medical Compendium

BACKGROUND: Health systems and payers require evidence that artificial intelligence (AI)-enabled decision support improves care delivery. Integrating AI into lung nodule management pathways may streamline workflows, improve identification and triage ... read more 

Allostatic load (AL), a composite measure of multisystem dysregulation associated with chronic stress, has been linked to lung cancer risk. However, its joint effects with genetic susceptibility and the biological pathways underlying this relationshi... read more 

BACKGROUND: Depression is a prevalent mental health condition that significantly affects individuals' well-being and daily functioning, making early depressive symptom detection crucial. OBJECTIVES: This study explores the potential of advancing spee... read more 

Norovirus, which is extremely contagious and has a significant impact on the gastrointestinal tract, has also been one of the main potential threats to health in the population. The use of fractional calculus has received much interest in the past fe... read more 

BACKGROUND: Dopamine agonist resistance is observed in 10%-30% of patients with prolactinomas, resulting in therapeutic failure and tumour progression. The molecular mechanisms underlying this resistance are not yet fully understood, highlighting the... read more 

Autonomous drone racing represents a major frontier in robotics research. It requires an artificial intelligence (AI) that can run onboard lightweight flying robots under tight resource and time constraints while pushing the physical system to its li... read more 

Electron-accepting chain reactions play crucial roles in diagnostics for bacterial infections, from nucleic acid amplification for bacterial identification to metabolic assays for phenotypic antibiotic susceptibility testing. When coupled with redox ... read more 

Producing alloys from recycled metals via secondary synthesis can markedly cut energy use, greenhouse-gas emissions, and dependence on scarce, strategically important elements relative to primary routes. The central obstacle is the feedstock itself: ... read more 

Quantifying biomorphological evolution and integrating phenotypic data into large-scale ecological and evolutionary studies are often limited by the scalability, subjectivity, and poor interpretability of existing methods. We introduce HAIKA (Hierarc... read more 

Integrated strategies to combat antibiotic-resistant bacteria and fungi require innovative commercial models, new discovery platforms, standardized genomic surveillance, and streamlined clinical trials. Machine learning and other new technologies wil... read more