AIMC Topic: Artificial Intelligence

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Pros, Cons and Limits of AI in Public Health.

Studies in health technology and informatics
This paper explores the role of Artificial Intelligence (AI) in Public Health (PH), examining its benefits, challenges, and ethical considerations. AI has become an essential tool in healthcare, improving diagnosis, treatment, and health system manag...

Bias Detection in Histology Images Using Explainable AI and Image Darkness Assessment.

Studies in health technology and informatics
The study underscores the importance of addressing biases in medical AI models to improve fairness, generalizability, and clinical utility. In this paper, we present a novel framework that combines Explainable AI (XAI) with image darkness assessment ...

Exploring the Role of Digital Twins in Heart Care: Research Directions and Applications.

Studies in health technology and informatics
The concept of digital twins has emerged as a transformative innovation in healthcare. Digital twins are virtual replicas of physical entities that can be updated with real-time data allowing for simulation analysis and optimization. Their applicatio...

Forecasting Banned Substances: Leveraging GNN and Explainable AI for Sports Anti-Doping.

Studies in health technology and informatics
Ensuring fairness in competitive sports requires robust mechanisms for detecting prohibited substances. Despite established regulations, challenges persist in accurately identifying new and emerging doping agents. This study introduces the use of Gra...

Real-World Deployment of a ML Pipeline for Pressure Wounds Prediction.

Studies in health technology and informatics
Hospital-acquired pressure injuries (HAPIs) are common complications that impact patient outcomes and strain healthcare resources. The Braden Scale is the standard tool for assessing HAPI risk, but it has limitations, including a high false-positive ...

Automatic Segmentation of Histopathological Glioblastoma Whole-Slide Images Utilizing MONAI.

Studies in health technology and informatics
Manual segmentation of histopathological images is both resource-intensive and prone to human error, particularly when dealing with challenging tumor types like Glioblastoma (GBM), an aggressive and highly heterogeneous brain tumor. The fuzzy borders...

Applications of machine learning and deep learning in musculoskeletal medicine: a narrative review.

European journal of medical research
Artificial intelligence (AI), with its technologies such as machine perception, robotics, natural language processing, expert systems, and machine learning (ML) with its subset deep learning, have transformed patient care and administration in all fi...

Feasibility study of automatic radiotherapy treatment planning for cervical cancer using a large language model.

Radiation oncology (London, England)
BACKGROUND: Radiotherapy treatment planning traditionally involves complex and time-consuming processes, often relying on trial-and-error methods. The emergence of artificial intelligence, particularly Large Language Models (LLMs), surpassing human c...

Evaluation of artificial intelligence (AI) chatbots for providing sexual health information: a consensus study using real-world clinical queries.

BMC public health
INTRODUCTION: Artificial Intelligence (AI) chatbots could potentially provide information on sensitive topics, including sexual health, to the public. However, their performance compared to nurses and across different AI chatbots, particularly in the...

A meta-analysis of the diagnostic test accuracy of artificial intelligence predicting emergency department dispositions.

BMC medical informatics and decision making
BACKGROUND: The rapid advancement of Artificial Intelligence (AI) has led to its widespread application across various domains, showing encouraging outcomes. Many studies have utilized AI to forecast emergency department (ED) disposition, aiming to f...