AIMC Topic: Artificial Intelligence

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Hydrogel-based sensors for multimodal health monitoring: from material design to intelligent sensing.

Nanoscale
Hydrogels, due to their biocompatibility, tunability, and stimulus responsiveness, are promising materials for flexible health monitoring. However, traditional hydrogel sensors suffer from various limitations in terms of long-term stability, signal f...

Application of artificial intelligence in predicting the results of open-heart surgery: a scoping review.

BMC medical informatics and decision making
PURPOSE: This scoping review aims to synthesize research on artificial intelligence (AI) in predicting open-heart surgery outcomes, evaluating AI model performance, and identifying gaps in data quality, algorithmic bias, and clinical applicability to...

Cracking the code: a head-to-head comparison of expert clinicians and artificial intelligence in diagnosing rare diseases.

Orphanet journal of rare diseases
BACKGROUND: Patients with rare diseases often face prolonged diagnostic journeys due to the low prevalence and diverse clinical presentations of these conditions. In Germany, specialized centers for rare diseases, established at university hospitals,...

Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study.

BMC medical education
BACKGROUND: Large language models (LLMs) like ChatGPT offer new ways to improve academic and administrative workflows in medical education, particularly for students studying in a language that is not their native tongue. We set out to examine whethe...

A methodology for developing dermatological datasets: lessons from retrospective data collection for AI-based applications.

BMC medical research methodology
PURPOSE: The integration of artificial intelligence into dermatological research has underscored the need for robust and well-structured dermatological datasets. However, these datasets vary widely in their development processes, and there is current...

Leveraging ChatGPT and explainable AI for enhancing clinical decision support.

Scientific reports
Large language models (LLMs) excel in many natural language processing tasks. However, their direct application to tabular, domain-specific clinical data remains challenging, as they lack innate mechanisms for reasoning over structured numerical feat...

Introducing FREM: a decision-support approach for automated identification of individuals at high imminent fracture risk.

Archives of osteoporosis
UNLABELLED: This study used explainable AI to improve the Danish FREM model for predicting one-year risk of major osteoporotic fractures in over 2.4 million individuals aged ≥ 45. A DART boosting algorithm improved performance (AUC 0.77), with explai...

From telepresence to intelligent convergence: mapping the global research landscape of remote robotic surgery (1980-2025).

Journal of robotic surgery
Remote robotic surgery (RRS) represents a frontier in surgical innovation, integrating robotics, artificial intelligence (AI), and high-speed communication networks. Despite its clinical significance, the global research landscape and conceptual evol...

Carbon dots meet artificial intelligence: applications in biomedical engineering.

Journal of materials chemistry. B
Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fie...