AIMC Topic: Humans

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Clinical Application of AI in Mammography: Insights from a Prospective Study.

Academic radiology
RATIONALE AND OBJECTIVES: This prospective study evaluated the performance of AI in a diagnostic clinic setting, comparing its effectiveness with radiologists of varying experience.

Machine Learning-Assisted Prediction of Persistent Incomplete Occlusion in Intracranial Aneurysms From Angiographic Parametric Imaging-Derived Features.

Academic radiology
RATIONALE AND OBJECTIVES: To develop machine-learning (ML) models incorporating angiographic parametric imaging (API)-derived parameters in predicting persistent incomplete occlusion of intracranial aneurysms (IAs) after flow diverter (FD) treatment.

Accelerating 3D radial MPnRAGE using a self-supervised deep factor model.

Magnetic resonance in medicine
PURPOSE: To develop a self-supervised and memory-efficient deep learning image reconstruction method for 4D non-Cartesian MRI with high resolution and a large parametric dimension.

MobileTurkerNeXt: investigating the detection of Bankart and SLAP lesions using magnetic resonance images.

Radiological physics and technology
The landscape of computer vision is predominantly shaped by two groundbreaking methodologies: transformers and convolutional neural networks (CNNs). In this study, we aim to introduce an innovative mobile CNN architecture designed for orthopedic imag...

Decision support using machine learning for predicting adequate bladder filling in prostate radiotherapy: a feasibility study.

Radiological physics and technology
This study aimed to develop a model for predicting the bladder volume ratio between daily CBCT and CT to determine adequate bladder filling in patients undergoing treatment for prostate cancer with external beam radiation therapy (EBRT). The model wa...

Macy Foundation Innovation Report Part I: Current Landscape of Artificial Intelligence in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
The rapid emergence of artificial intelligence (AI), including generative large language models, offers transformative opportunities in medical education. This proliferation has generated numerous speculative discussions about AI's promise but has be...

NPI-HetGNN: A Prediction Model of ncRNA-Protein Interactions Based on Heterogeneous Graph Neural Networks.

Interdisciplinary sciences, computational life sciences
Non-coding RNAs (ncRNAs) are one of the components of epigenetic mechanisms that regulates gene expression. Studying ncRNA-protein interactions (NPI) can help to explore a wide range of biological features and related diseases. Traditional NPI resear...

Recent advances in diagnostic technologies for postoperative central nervous system infections: a review.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Postoperative central nervous system infections (PCNSIs), including meningitis, cerebral abscesses, and implant-associated infections, represent critical complications following neurosurgical procedures. These infections pose significant risks to pat...

Recent advances in monoclonal antibody development for treatment of B-cell acute lymphoblastic leukemia.

Leukemia & lymphoma
Monoclonal antibody (mAb)-based therapies targeting CD19, CD20, and CD22 have revolutionized B-ALL treatment, offering precision and reduced systemic toxicity by engaging immune mechanisms to eliminate leukemic cells. This review synthesizes literatu...

Artificial intelligence in prediction of postpartum hemorrhage: a primer and review.

International journal of obstetric anesthesia
Postpartum hemorrhage (PPH) is a leading cause of maternal mortality worldwide, and the ability to predict PPH may help address preventable causes of morbidity and mortality such as delays in care. Understanding the importance of standardized approac...