AIMC Topic: Artificial Intelligence

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A Computational Framework for Tailored Preventive Care Recommendations Using Electronic Health Records.

Studies in health technology and informatics
Most healthcare systems worldwide are designed to be reactive. According to the U.S. Centers for Disease Control and Prevention (CDC), 90% of the nation's $3.3 trillion annual healthcare expenditures are attributed to individuals with chronic and men...

AI-Assisted Detection Support for Middle Ear Diseases Using Multimodal Large Language Models.

Studies in health technology and informatics
Middle ear diseases, such as otitis media and middle ear effusion, are difficult to accurately detect in primary care. We developed an AI-powered system using Azure OpenAI's GPT-4 Vision, the first multimodal large language model (LLM) applied to ana...

Research Trends and Focus of Trust in Healthcare-Based AI: A Co-Occurrence Analysis and Modified Scoping Review.

Studies in health technology and informatics
BACKGROUND: As the potential of artificial intelligence (AI) in healthcare (HC) grows, so too does the number of potential risks, which has contributed to the development of regulations at national and international level that specifically address tr...

Role of AI in Clinical Decision-Making: An Analysis of FDA Medical Device Approvals.

Studies in health technology and informatics
The U.S. Food and Drug Administration (FDA) plays an important role in ensuring safety and effectiveness of AI/ML-enabled devices through its regulatory processes. In recent years, there has been an increase in the number of these devices cleared by ...

The Unintended Harm of Artificial Intelligence (AI): Exploring Critical Incidents of AI in Healthcare.

Studies in health technology and informatics
Artificial intelligence (AI) has been utilized in healthcare for years, presenting various risks. However, there is a gap in understanding AI incidents, particularly their impacts and associated risks. This study provides an overview of AI-related in...

Detecting and Classifying Mycetoma in Histopathological Images Using DenseNet and U-Net.

Studies in health technology and informatics
Mycetoma, recognised by the WHO as a Neglected Tropical Disease, has significant diagnostic hurdles which lead to severe health consequences. Mycetoma can be caused by certain types of bacteria (actinomycetoma) or fungi (eumycetoma). Identifying whet...

Fada: Fetal Accurate Detection AI for Automated Ultrasound Image Analysis and Reporting.

Studies in health technology and informatics
This study introduces Fetal Accurate Detection AI (FADA) an advanced AI-driven framework for generating clinically relevant descriptions from fetal ultrasound images, specifically focused on diverse anatomical structures and views, including trans-ab...

Integrating Artificial Intelligence into Mixed Reality for Back Detection and Virtual 3D Spine Visualization on Scoliosis Patients.

Studies in health technology and informatics
Adolescent Idiopathic Scoliosis is a complex three-dimensional spinal deformity that typically develops between the ages of 10 and 18 years. If untreated, this condition can significantly impair a patient's quality of life and functional capabilities...

Automate Creating, Customizing, and Optimizing Comorbidity Indices Using a Data-Driven AI/ML Approach.

Studies in health technology and informatics
Due to individual differences in severity of illness, clinical studies typically use a comorbidity index to adjust outcomes. With the increasing use of electronic health records (EHRs) to assess the quality of care, a key question arises: how to adju...

A Scoping Review of AI/ML Algorithm Updating Practices for Model Continuity and Patient Safety Using a Simplified Checklist.

Studies in health technology and informatics
The ubiquity of clinical artificial intelligence (AI) and machine learning (ML) models necessitates measures to ensure the reliability of model output over time. Previous reviews have highlighted the lack of external validation for most clinical mode...