AIMC Topic: Humans

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BrainSegFounder: Towards 3D foundation models for neuroimage segmentation.

Medical image analysis
The burgeoning field of brain health research increasingly leverages artificial intelligence (AI) to analyze and interpret neuroimaging data. Medical foundation models have shown promise of superior performance with better sample efficiency. This wor...

SDF4CHD: Generative modeling of cardiac anatomies with congenital heart defects.

Medical image analysis
Congenital heart disease (CHD) encompasses a spectrum of cardiovascular structural abnormalities, often requiring customized treatment plans for individual patients. Computational modeling and analysis of these unique cardiac anatomies can improve di...

UC-Hybrid: Uncertainty-based contrastive learning on hybrid network for medical image segmentation.

Computer methods and programs in biomedicine
Medical image segmentation has made remarkable progress with advances in deep learning technology, depending on the quality and quantity of labeled data. Although various deep learning model structures and training methods have been proposed and high...

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...

Significance of plasma p-tau217 in predicting long-term dementia risk in older community residents: Insights from machine learning approaches.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Whether plasma biomarkers play roles in predicting incident dementia among the general population is worth exploring.

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...

[Healthcare 4.0-Medicine in transition].

Herz
Healthcare 4.0 describes the future transformation of the healthcare sector driven by the combination of digital technologies, such as artificial intelligence (AI), big data and the Internet of Medical Things, enabling the advancement of precision me...

PolypNextLSTM: a lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM.

International journal of computer assisted radiology and surgery
PURPOSE: Commonly employed in polyp segmentation, single-image UNet architectures lack the temporal insight clinicians gain from video data in diagnosing polyps. To mirror clinical practices more faithfully, our proposed solution, PolypNextLSTM, leve...