AIMC Topic: Radiologists

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Radiology Staff Experiences With Integrating Artificial Intelligence Into Radiology Practice in a Swedish Hospital: Qualitative Case Study.

JMIR formative research
BACKGROUND: The integration of artificial intelligence (AI) in radiology has advanced significantly, but research on how it affects the daily work of radiology staff is limited.

Assessing the Accuracy of Artificial Intelligence in Detecting Intracranial Aneurysms in a Clinical Setting Relative to Neuroradiologists.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Intracranial aneurysms (IAs), detected in 2%-5% of the population, represent a major health care issue because ruptured aneurysms with resultant hemorrhage are associated with severe morbidity or mortality. With the increasing...

Workload of diagnostic radiologists in the foreseeable future based on recent (2024) scientific advances: Updated growth expectations.

European journal of radiology
PURPOSE: To assess the expected impact of the 2024 medical imaging literature on the workload of diagnostic radiologists.

Integration of artificial intelligence in radiology education: a requirements survey and recommendations from faculty radiologists, residents, and medical students.

BMC medical education
BACKGROUND: To investigate the perspectives and expectations of faculty radiologists, residents, and medical students regarding the integration of artificial intelligence (AI) in radiology education, a survey was conducted to collect their opinions a...

Economics of AI and human task sharing for decision making in screening mammography.

Nature communications
The rising global incidence of breast cancer and the persistent shortage of specialized radiologists have heightened the demand for innovative solutions in mammography screening. Artificial intelligence (AI) has emerged as a promising tool to bridge ...

The radiologist as an independent "third party" to the patient and clinicians in the era of generative AI.

La Radiologia medica
Radiologists are crucial in the diagnostic workflow. They must maintain an independent perspective, being a "third party" to the patients and referral clinicians. This is important when documenting the absence of relevant abnormalities or providing i...

Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?

La Radiologia medica
The advances in artificial intelligence (AI) technology in recent years have been remarkable, and the field of radiology is at the forefront of applying and implementing these technologies in daily clinical practice. Radiologists must keep up with th...

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
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...

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

European journal of radiology
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 ...