Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 2,731 to 2,740 of 235,381 articles

Towards data-driven refinement of an automated cluster alert system: assessing the concordance of epidemiological expert assessment and genotyping.

Infection control and hospital epidemiology
OBJECTIVE: An automated CLuster AleRt system (CLAR) is employed at our hospital to detect clusters of relevant microorganisms. Alerts are subsequently assessed by infection prevention and control (IPC) experts to determine their epidemiological relev... read more 

Conformity Between Values and EU Legal Requirements Regarding an AI Clinical Decision Support System (AI-CDSS) for Improved Cardiovascular Risk Management (DECIDE).

The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics
The European Union Artificial Intelligence (AI) Act was adopted in 2024 to protect public interests from AI-related harms. We aimed to determine whether the AI Act captures the most relevant values of stakeholders (understood as any person potentiall... read more 

When AI meets DEI: Employee AI-beliefs and their implications for workplace diversity, equity, and inclusion.

Current opinion in psychology
As artificial intelligence (AI) reshapes the workplace, its impact on diversity, equity, and inclusion (DEI) has been examined primarily through the lens of what AI actually does (i.e., system design, outputs). This review shifts the focus to humans'... read more 

A mature tertiary lymphoid structure-associated spatial niche is inversely associated with ACC1-related lipid metabolism in neoadjuvant-treated hepatocellular carcinoma.

Translational oncology
Tumor heterogeneity in hepatocellular carcinoma (HCC) is shaped by spatially organized immune and metabolic ecosystems that may influence therapeutic response. However, how mature tertiary lymphoid structure (TLS) niches relate to tumor metabolic het... read more 

Understanding preferences for explainable AI: A study on LIME variations.

Applied ergonomics
The current research aims to empirically examine user preferences of four variations of visual explanations from an image classification model. Participants (N = 23) were recruited from a Midwestern university. The study was a within-subjects design ... read more 

Evaluating multimodal explainable adaptive learning in university EFL education: Learner outcomes, teacher oversight, and implementation conditions.

Acta psychologica
Artificial intelligence (AI) offers substantial potential for personalized English as a Foreign Language (EFL) instruction, yet concerns remain regarding the transparency of adaptive recommendations, the fragmentation of learner data, and the preserv... read more 

Soil carbon and inundation regimes jointly regulate denitrification potential in restored riverine floodplains.

Journal of environmental management
Denitrification plays a key role in nitrogen removal in restored floodplains, yet the relative importance of inundation regimes, hydrogeomorphic setting, and soil properties remains uncertain. In this study, we evaluated the environmental controls on... read more 

Research progress on the mechanism and clinical significance of immunoediting in the malignant transformation of oral leukoplakia.

International immunopharmacology
The insidious malignant transformation of oral leukoplakia (OLK) into oral squamous cell carcinoma (OSCC) represents a critical clinical bottleneck in head and neck oncology. Grounded in the cancer immunoediting theory of "elimination-equilibrium-esc... read more 

Evaluating imputation methods for longitudinal clinical trajectories: Toxicities in head and neck cancer treatment.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Longitudinally collected medical data is often afflicted by missingness, making methods mitigating missingness valuable. This study evaluated nine imputation methods for longitudinal data, using toxicity scores measured at multiple timepoint... read more 

Limits of Machine Learning for Predicting Stillbirth at Term: A Population-Based Cohort of 302,192 Pregnancies in Northern Italy.

American journal of obstetrics & gynecology MFM
BACKGROUND: Stillbirth at term is a major public-health concern. In high-income settings, the most commonly identifiable causes are unrecognised fetal growth restriction (about 14%) and placental abruption (about 12%), but 20 to 40% of term stillbirt... read more