AIMC Topic: Data Accuracy

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Who should decide how limited healthcare resources are prioritized? Autonomous technology as a compelling alternative to humans.

PloS one
Who should decide how limited resources are prioritized? We ask this question in a healthcare context where patients must be prioritized according to their need and where advances in autonomous artificial intelligence-based technology offer a compell...

Performance of ChatGPT on Chinese national medical licensing examinations: a five-year examination evaluation study for physicians, pharmacists and nurses.

BMC medical education
BACKGROUND: Large language models like ChatGPT have revolutionized the field of natural language processing with their capability to comprehend and generate textual content, showing great potential to play a role in medical education. This study aime...

Analyzing the influential factors of process safety culture by hybrid hidden content analysis and fuzzy DEMATEL.

Scientific reports
Due to the complex nature of safety culture and process industries, several factors influence process safety culture. This paper presents a novel framework that combines the hidden content analysis method with Decision Making Trial and Evaluation Lab...

Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey.

The Laryngoscope
INTRODUCTION: Accuracy and validity of voice AI algorithms rely on substantial quality voice data. Although commensurable amounts of voice data are captured daily in voice centers across North America, there is no standardized protocol for acoustic d...

A Conference (Missingness in Action) to Address Missingness in Data and AI in Health Care: Qualitative Thematic Analysis.

Journal of medical Internet research
BACKGROUND: Missingness in health care data poses significant challenges in the development and implementation of artificial intelligence (AI) and machine learning solutions. Identifying and addressing these challenges is critical to ensuring the con...

We're implementing AI now, so why not ask us what to do? - How AI providers perceive and navigate the spread of diagnostic AI in complex healthcare systems.

Social science & medicine (1982)
Despite high expectations of artificial intelligence (AI) in medical diagnostics, predictions of its extensive and rapid adoption have so far not been matched by reality. AI providers seeking to promote and perpetuate the use of this technology are f...

An investigation study on the interpretation of ultrasonic medical reports using OpenAI's GPT-3.5-turbo model.

Journal of clinical ultrasound : JCU
OBJECTIVES: Ultrasound medical reports are an important means of diagnosing diseases and assessing treatment effectiveness. However, their professional terms and complex sentences often make it difficult for ordinary people to understand. Therefore, ...

Influence on the accuracy in ChatGPT: Differences in the amount of information per medical field.

International journal of medical informatics
OBJECTIVES: Although ChatGPT was not developed for medical use, there is growing interest in its use in medical fields. Understanding its capabilities and precautions for its use in the medical field is an urgent matter. We hypothesized that differen...

Deep Generative Models: The winning key for large and easily accessible ECG datasets?

Computers in biology and medicine
Large high-quality datasets are essential for building powerful artificial intelligence (AI) algorithms capable of supporting advancement in cardiac clinical research. However, researchers working with electrocardiogram (ECG) signals struggle to get ...

Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The scarcity of high-quality annotated data is omnipresent in machine learning. Especially in biomedical segmentation applications, experts need to spend a lot of their time into annotating due to the complexity. Hence, methods to reduce s...