Medical Education

Digital transformation of nephrology POCUS education-Integrating a multiagent, artificial intelligence, and human collaboration-enhanced curriculum with expert feedback.

BACKGROUND: The digital transformation in medical education is reshaping how clinical skills, such as point-of-care ultrasound (POCUS), are taught. In nephrology fellowship programs, POCUS is essential for enhancing diagnostic accuracy, guiding procedures, and optimizing patient management. To address these evolving demands, we developed an artificial intelligence (AI)-driven POCUS curriculum usin...

Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound.

Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, developing an automated system for nodule segmentation can enhance user independence and expedite clinical analysis. Unlike fully-supervised learning, weakly-supervised segmentation (WSS) can streamline the laborious and ...

Performance of Plug-In Augmented ChatGPT and Its Ability to Quantify Uncertainty: Simulation Study on the German Medical Board Examination.

BACKGROUND: The GPT-4 is a large language model (LLM) trained and fine-tuned on an extensive dataset. After the public release of its predecessor in N...

Infusing Multi-Hop Medical Knowledge Into Smaller Language Models for Biomedical Question Answering.

MedQA-USMLE is a challenging biomedical question answering (BQA) task, as its questions typically involve multi-hop reasoning. To solve this task, BQA...

Weighted Multi-Modal Contrastive Learning Based Hybrid Network for Alzheimer's Disease Diagnosis.

Multiple imaging modalities and specific proteins in the cerebrospinal fluid, providing a comprehensive understanding of neurodegenerative disorders, ...

A hybrid vine copula-fuzzy model for groundwater level simulation under uncertainty.

Accurate simulation of groundwater level is crucial for the sustainable management of water resources. However, the numerous uncertainties in input da...

Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning.

We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural c...

Enhancing Patient-Physician Communication: Simulating African American Vernacular English in Medical Diagnostics with Large Language Models.

UNLABELLED: Effective communication is crucial in reducing health disparities. However, linguistic differences, such as African American Vernacular En...

Leveraging Generative Artificial Intelligence to Improve Motivation and Retrieval in Higher Education Learners.

Generative artificial intelligence (GenAI) presents novel approaches to enhance motivation, curriculum structure and development, and learning and ret...

The Road Map for ACR Practice Accreditation for Radiology Artificial Intelligence.

As the use of artificial intelligence (AI) continues to grow in radiology, it has become clear that its real-world performance often differs from that...

Uncovering key sources of regional ozone simulation biases using machine learning and SHAP analysis.

Atmospheric chemical transport models (CTMs) are widely used in air quality management, but still have large biases in simulations. Accurately and eff...

Exploring Curriculum Considerations to Prepare Future Radiographers for an AI-Assisted Health Care Environment: Protocol for Scoping Review.

BACKGROUND: The use of artificial intelligence (AI) technologies in radiography practice is increasing. As this advanced technology becomes more embed...

Integrating Artificial Intelligence Technology Into Simulation for Pre- and Postlicensure Nursing Students.

Advances in artificial intelligence (AI) technologies have not been widely integrated into simulation education. This work examines the process of des...

Developing a real-time water quality simulation toolbox using machine learning and application programming interface.

Rivers are vital for sustaining human life as they foster social development, provide drinking water, maintain aquatic ecosystems, and offer recreatio...

Exploring the potential of artificial intelligence chatbots in prosthodontics education.

BACKGROUND: The purpose of this study was to evaluate the performance of widely used artificial intelligence (AI) chatbots in answering prosthodontics...

Utilization and perception of generative artificial intelligence by medical students in residency applications.

After completing medical school in the United States, most students apply to residency programs to progress in their training. The residency applicati...

Building Trust with AI: How Essential is Validating AI Models in the Therapeutic Triad of Therapist, Patient, and Artificial Third? Comment on What is the Current and Future Status of Digital Mental Health Interventions?

Since the publication of "What is the Current and Future Status of Digital Mental Health Interventions?" the exponential growth and widespread adoptio...

Minimally invasive modalities for keratinocyte carcinomas-Part I: Diagnostics.

Keratinocyte carcinoma, including basal cell and squamous cell carcinoma, is the most prevalent form of cancer within the United States, with its inci...

Artificial Intelligence Meets Holistic Review: Promises and Pitfalls of Automating the Medical Education Admissions Process.

Holistic review has been widely adopted in medical education as a means of promoting equity in the application process and diversity in the medical wo...

Enhancing diagnostic accuracy of thyroid nodules: integrating self-learning and artificial intelligence in clinical training.

PURPOSE: This study explores a self-learning method as an auxiliary approach in residency training for distinguishing between benign and malignant thy...