Radiologists

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study.

JMIR formative research 39727232

BACKGROUND: Home hospitalization is a care modality growing in popularity worldwide. Telemedicine-driven hospital-at-home (HAH) services could replace traditional hospital departments for selected patients. Chest x-rays typically serve as a key diagn...

Aged Aged, 80 and over Artificial Intelligence Consensus Female Home Care Services Humans Internal Medicine Male Prospective Studies Radiography, Thoracic Radiologists Software

View on PubMed DOI

Incorporating Radiologist Knowledge Into MRI Quality Metrics for Machine Learning Using Rank-Based Ratings.

Journal of magnetic resonance imaging : JMRI 39690114

BACKGROUND: Deep learning (DL) often requires an image quality metric; however, widely used metrics are not designed for medical images.

Algorithms Brain Databases, Factual Deep Learning Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Machine Learning Magnetic Resonance Imaging Neural Networks, Computer Radiologists Reproducibility of Results Retrospective Studies

View on PubMed DOI

Large language models in methodological quality evaluation of radiomics research based on METRICS: ChatGPT vs NotebookLM vs radiologist.

European journal of radiology 39938163

OBJECTIVES: This study aimed to evaluate the effectiveness of large language models (LLM) in assessing the methodological quality of radiomics research, using METhodological RadiomICs Score (METRICS) tool.

Biomedical Research Generative Artificial Intelligence Humans Language Large Language Models Natural Language Processing Radiologists Radiology Radiomics Reproducibility of Results

View on PubMed DOI

AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.

PloS one 39854592

To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings for rib fractures (RFs) detection on CT images. This study included 243 consecutive chest trauma pat...

Adult Aged Aged, 80 and over Artificial Intelligence Female Humans Male Middle Aged Radiographic Image Interpretation, Computer-Assisted Radiologists Rib Fractures Sensitivity and Specificity Tomography, X-Ray Computed

View on PubMed DOI

Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.

JMIR formative research 39842001

BACKGROUND: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions ...

Clinical Competence Diagnostic Errors Eye Movements Eye-Tracking Technology Humans Machine Learning Radiologists

View on PubMed DOI

Diagnostic Performance of Different Examination Types and Learning Curves of Radiologists for 5G-Based Robot-Assisted Tele-Ultrasonography: A Prospective and Large-Scale Study.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine 39838951

OBJECTIVE: To investigate the feasibility of remotely providing routine ultrasound (US) examinations to patients using a fifth-generation-based robot-assisted tele-ultrasonography (RATU) system in a real-world setting.

Adult Aged Aged, 80 and over China Clinical Competence Feasibility Studies Female Humans Learning Curve Male Middle Aged Prospective Studies Radiologists Robotics Telemedicine Ultrasonography Young Adult

View on PubMed DOI

Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.

AJR. American journal of roentgenology 39772578

Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluation; such studies do not capture the full extent of missed fractures. The purpose of this study was ...

Adult Aged Cervical Vertebrae Diagnostic Errors Female Humans Machine Learning Male Middle Aged Missed Diagnosis Radiologists Retrospective Studies Spinal Fractures Tomography, X-Ray Computed

View on PubMed DOI

Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.

European journal of radiology 39983597

PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines. Chest contrast-enhanced computed tomography (CECT) is crucial in the ...

Adult Aged Algorithms Female Humans Hypertension, Pulmonary Machine Learning Male Middle Aged Radiographic Image Interpretation, Computer-Assisted Radiologists Reproducibility of Results Retrospective Studies Sensitivity and Specificity Tomography, X-Ray Computed

View on PubMed DOI

Aligning large language models with radiologists by reinforcement learning from AI feedback for chest CT reports.

European journal of radiology 39954322

BACKGROUND: Large language models (LLMs) often struggle to fully capture the nuanced preferences and clinical judgement of radiologists in medical report summarization even when fine-tuned on massive medical reports. This could lead to the generated ...

Aged Artificial Intelligence Feedback Female Humans Large Language Models Machine Learning Male Middle Aged Radiography, Thoracic Radiologists Reinforcement, Psychology Retrospective Studies Tomography, X-Ray Computed

View on PubMed DOI

Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine 39953921

OBJECTIVE: To develop, test, and externally validate a hybrid artificial intelligence (AI) model based on hand-crafted and deep radiomics features extracted from B-mode ultrasound images in differentiating benign and malignant thyroid nodules compare...

Adult Aged Artificial Intelligence Cohort Studies Diagnosis, Differential Female Humans Image Interpretation, Computer-Assisted Iran Malaysia Male Middle Aged Radiologists Radiomics Reproducibility of Results Thyroid Gland Thyroid Neoplasms Thyroid Nodule Ultrasonography

View on PubMed DOI

AI Medical Compendium Topic

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

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study.

Incorporating Radiologist Knowledge Into MRI Quality Metrics for Machine Learning Using Rank-Based Ratings.

Large language models in methodological quality evaluation of radiomics research based on METRICS: ChatGPT vs NotebookLM vs radiologist.

AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.

Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.

Diagnostic Performance of Different Examination Types and Learning Curves of Radiologists for 5G-Based Robot-Assisted Tele-Ultrasonography: A Prospective and Large-Scale Study.

Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.

Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.

Aligning large language models with radiologists by reinforcement learning from AI feedback for chest CT reports.

Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.

Popular Topics

Recent Journals