AIMC Topic: Artificial Intelligence

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A comprehensive overview of barriers and strategies for AI implementation in healthcare: Mixed-method design.

PloS one
Implementation of artificial intelligence systems for healthcare is challenging. Understanding the barriers and implementation strategies can impact their adoption and allows for better anticipation and planning. This study's objective was to create ...

Improving ED admissions forecasting by using generative AI: An approach based on DGAN.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Generative Deep Learning has emerged in recent years as a significant player in the Artificial Intelligence field. Synthesizing new data while maintaining the features of reality has revolutionized the field of Deep Learning...

Combining Image Similarity and Predictive Artificial Intelligence Models to Decrease Subjectivity in Thyroid Nodule Diagnosis and Improve Malignancy Prediction.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVES: To evaluate the efficacy of combining predictive artificial intelligence (AI) and image similarity model to risk stratify thyroid nodules, using retrospective external validation study.

Mavacamten in hypertrophic obstructive cardiomyopathy: Prospects for AI integration and mitigating healthcare disparities.

Current problems in cardiology
Hypertrophic obstructive cardiomyopathy (HOCM) is an autosomal dominant condition that still remains significantly under-diagnosed worldwide. Early detection through clinical evaluation, imaging, and familial history is crucial to prevent severe comp...

Generative Artificial Intelligence and Large Language Models in Primary Care Medical Education.

Family medicine
Generative artificial intelligence and large language models are the continuation of a technological revolution in information processing that began with the invention of the transistor in 1947. These technologies, driven by transformer architectures...

Development of an artificial intelligence-based algorithm for predicting the severity of myxomatous mitral valve disease from thoracic radiographs by using two grading systems.

Research in veterinary science
A heart-convolutional neural network (heart-CNN) was designed and tested for the automatic classification of chest radiographs in dogs affected by myxomatous mitral valve disease (MMVD) at different stages of disease severity. A retrospective and mul...

Video-Based Performance Analysis in Pituitary Surgery - Part 2: Artificial Intelligence Assisted Surgical Coaching.

World neurosurgery
BACKGROUND: Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed...

Artificial Intelligence and Machine Learning for Inborn Errors of Immunity: Current State and Future Promise.

The journal of allergy and clinical immunology. In practice
Artificial intelligence (AI) and machine learning (ML) research within medicine has exponentially increased over the last decade, with studies showcasing the potential of AI/ML algorithms to improve clinical practice and outcomes. Ongoing research an...

Artificial intelligence methods available for cancer research.

Frontiers of medicine
Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience...

Preparing for Artificial General Intelligence (AGI) in Health Professions Education: AMEE Guide No. 172.

Medical teacher
Generative Artificial Intelligence (GenAI) caught Health Professions Education (HPE) institutions off-guard, and they are currently adjusting to a changed educational environment. On the horizon, however, is Artificial Intelligence (AGI) which promi...