AIMC Topic: Humans

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Comparison of deep learning models to detect crossbites on 2D intraoral photographs.

Head & face medicine
BACKGROUND: To support dentists with limited experience, this study trained and compared six convolutional neural networks to detect crossbites and classify non-crossbite, frontal, and lateral crossbites using 2D intraoral photographs.

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...

Selection of data analytic techniques by using fuzzy AHP TOPSIS from a healthcare perspective.

BMC medical informatics and decision making
The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with differen...

Impact of acquisition area on deep-learning-based glaucoma detection in different plexuses in OCTA.

Scientific reports
Glaucoma is a group of neurodegenerative diseases that can lead to irreversible blindness. Yet, the progression can be slowed down if diagnosed and treated early enough. Optical coherence tomography angiography (OCTA) can non-invasively provide valua...

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...

Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities.

Nature communications
Multi-sequence magnetic resonance imaging is crucial in accurately identifying knee abnormalities but requires substantial expertise from radiologists to interpret. Here, we introduce a deep learning model incorporating co-plane attention across imag...

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...