AIMC Topic: Artificial Intelligence

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Prognostication in patients with idiopathic pulmonary fibrosis using quantitative airway analysis from HRCT: a retrospective study.

The European respiratory journal
BACKGROUND: Predicting shorter life expectancy is crucial for prioritising antifibrotic therapy in fibrotic lung diseases (FLDs), where progression varies widely, from stability to rapid deterioration. This heterogeneity complicates treatment decisio...

Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

International journal of medical informatics
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), or pneumonia, which are often misdiagnosed. We aimed to create...

Show and tell: A critical review on robustness and uncertainty for a more responsible medical AI.

International journal of medical informatics
This critical review explores two interrelated trends: the rapid increase in studies on machine learning (ML) applications within health informatics and the growing concerns about the reproducibility of these applications across different healthcare ...

Artificial intelligence in tobacco control: A systematic scoping review of applications, challenges, and ethical implications.

International journal of medical informatics
BACKGROUND: Tobacco use remains a significant global health challenge, contributing substantially to preventable morbidity and mortality. Despite established interventions, outcomes vary due to scalability issues, resource constraints, and limited re...

Machine learning and explainable artificial intelligence reveals the MicroRNAs associated with survival of head and neck squamous cell carcinoma patients.

Computational biology and chemistry
Dysregulated microRNAs (miRNAs) play a significant role in cancer development and metastasis. In literature, miRNAs have been used for the survival prediction of different types of cancers using AI. Although AI is useful for diagnosis and prognosis p...

Comparison of CT referral justification using clinical decision support and large language models in a large European cohort.

European radiology
BACKGROUND: Ensuring appropriate use of CT scans is critical for patient safety and resource optimization. Decision support tools and artificial intelligence (AI), such as large language models (LLMs), have the potential to improve CT referral justif...

Can Artificial Intelligence Language Models Effectively Address Dental Trauma Questions?

Dental traumatology : official publication of International Association for Dental Traumatology
BACKGROUND/AIM: Artificial intelligence (AI) chatbots, also known as large language models (LLMs), have become increasingly common educational tools in healthcare. Although the use of LLMs for emergency dental trauma is gaining popularity, it is cruc...

Why is AI Not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling.

IEEE transactions on visualization and computer graphics
This paper explores the potential for human-AI collaboration in the context of data storytelling for data workers. Data storytelling communicates insights and knowledge from data analysis. It plays a vital role in data workers' daily jobs since it bo...