AIMC Topic: Artificial Intelligence

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Encompassing trust in medical AI from the perspective of medical students: a quantitative comparative study.

BMC medical ethics
BACKGROUND: In the years to come, artificial intelligence will become an indispensable tool in medical practice. The digital transformation will undoubtedly affect today's medical students. This study focuses on trust from the perspective of three gr...

Comparative analysis of artificial intelligence and expert assessments in detecting neonatal procedural pain.

Scientific reports
Assessing pain in newborns in the NICU is crucial due to their frequent exposure to painful stimuli, yet it's challenging due to the subjective nature of current methods. This study aimed to evaluate the effectiveness of an AI system designed for aut...

An international study presenting a federated learning AI platform for pediatric brain tumors.

Nature communications
While multiple factors impact disease, artificial intelligence (AI) studies in medicine often use small, non-diverse patient cohorts due to data sharing and privacy issues. Federated learning (FL) has emerged as a solution, enabling training across h...

Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions.

BMC medicine
The integration of machine learning (ML) and artificial intelligence (AI) techniques in life-course epidemiology offers remarkable opportunities to advance our understanding of the complex interplay between biological, social, and environmental facto...

In human-machine trust, humans rely on a simple averaging strategy.

Cognitive research: principles and implications
With the growing role of artificial intelligence (AI) in our lives, attention is increasingly turning to the way that humans and AI work together. A key aspect of human-AI collaboration is how people integrate judgements or recommendations from machi...

Preoperative prediction model of lymph node metastasis in the inguinal and femoral region based on radiomics and artificial intelligence.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society
OBJECTIVE: To predict preoperative inguinal lymph node metastasis in vulvar cancer patients using a machine learning model based on imaging features and clinical data from pelvic magnetic resonance imaging (MRI).

Danger, Danger, Gaston Labat! Does zero-shot artificial intelligence correlate with anticoagulation guidelines recommendations for neuraxial anesthesia?

Regional anesthesia and pain medicine
INTRODUCTION: Artificial intelligence and large language models (LLMs) have emerged as potentially disruptive technologies in healthcare. In this study GPT-3.5, an accessible LLM, was assessed for its accuracy and reliability in performing guideline-...

The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates.

Annual review of vision science
Inferences made about objects via vision, such as rapid and accurate categorization, are core to primate cognition despite the algorithmic challenge posed by varying viewpoints and scenes. Until recently, the brain mechanisms that support these capab...