Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 70,481 to 70,490 of 234,131 articles

Artificial Intelligence and Machine Learning for Osteoarthritis and Cartilage Assessment.

Radiologic clinics of North America
Osteoarthritis (OA) affects over 500 million people globally and poses diagnostic and management challenges due to its complex pathophysiology. Artificial intelligence (AI) and machine learning, particularly deep learning, are revolutionizing musculo... read more 

Using ChatGPT to Engage Generation Z With Historical Nursing Theorists.

The Journal of nursing education
BACKGROUND: Rousing Generation Z's (Gen Z) interest in historical nursing theorists presents a challenge for nurse educators. An innovative method for engaging Gen Z with historical figures in nursing involves the use of artificial intelligence. METH... read more 

Spatially resolved airway niches: mapping epithelial-immune microenvironments in asthma.

Expert review of respiratory medicine
INTRODUCTION: Spatially resolved omics has reconceptualized the bronchial wall as a mosaic of epithelial - immune microenvironments whose local molecular circuits drive asthma heterogeneity and medication responsiveness. AREAS COVERED: We searched Pu... read more 

Development and validation of a machine learning model for accurate detection of wrong blood in tube errors in hospitalized patients.

Clinical chemistry and laboratory medicine
OBJECTIVES: To develop and validate a machine-learning model based on routinely available biochemical and hematological parameters for detecting wrong blood in tube (WBIT) errors in hospitalized patients. METHODS: A retrospective multicenter study in... read more 

Artificial Intelligence for CT and MRI Protocoling: A Meta-Analysis of Traditional Machine Learning, BERT, and Large Language Models.

AJR. American journal of roentgenology
Background: Examination protocoling is a resource-intensive task. Various artificial intelligence (AI) approaches have been investigated to automate this process. Objective: To evaluate performance of traditional machine-learning (ML) models, bidirec... read more 

Integrated multi-task learning framework for hepatocellular carcinoma segmentation and histological grading using fused multi-phase MRI.

Abdominal radiology (New York)
OBJECTIVE: This study aims to develop and validate an integrated multi-task framework for hepatocellular carcinoma analysis by combining deep learning-based segmentation with radiomics-based histological grading using fused multi-phase MRI. MATERIALS... read more 

Leveraging quantum chemical properties in transfer learning for predicting blood-brain barrier permeability of drugs.

Drug delivery and translational research
The blood-brain barrier (BBB), crucial for central nervous system (CNS) homeostasis, poses challenges for drug delivery in CNS diseases due to selective permeability. Because of this difficulty, there are limited treatments developed for CNS diseases... read more