AIMC Topic: Radiologists
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Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.
Journal of imaging informatics in medicine
Oct 10, 2024
The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and speci...
Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.
Annals of surgical oncology
Oct 5, 2024
OBJECTIVES: This study was designed to assess computed tomography (CT)-based radiomics of colorectal liver metastases (CRLM), extracted from posttreatment scans in estimating pathologic treatment response to neoadjuvant therapy, and to compare treatm...
Prognosis
Retrospective Studies
Tomography, X-Ray Computed
Female
Humans
Machine Learning
Male
Middle Aged
Liver Neoplasms
Antineoplastic Combined Chemotherapy Protocols
Aged
Adult
Colorectal Neoplasms
Radiomics
Neoadjuvant Therapy
Follow-Up Studies
Radiologists
Response Evaluation Criteria in Solid Tumors
Clinical Impact of Radiologist's Alert System on Patient Care for High-risk Incidental CT Findings: A Machine Learning-Based Risk Factor Analysis.
Academic radiology
Oct 4, 2024
RATIONALE AND OBJECTIVES: Efficient communication between radiologists and clinicians ordering computed tomography (CT) examinations is crucial for managing high-risk incidental CT findings (ICTFs). Herein, we introduced a Radiologist's Alert and Pat...
Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.
Scientific reports
Sep 28, 2024
The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improv...
The legal regulation of artificial intelligence in the European Union: A practical guide for radiologists.
Radiologia
Sep 24, 2024
The European Union is taking the lead globally on the regulation of Artificial Intelligence (AI) and developing important legislation, namely the AI Act. The purpose of this article is to describe this regulation and examine three implications that w...
Evolution of radiology staff perspectives during artificial intelligence (AI) implementation for expedited lung cancer triage.
Clinical radiology
Sep 21, 2024
AIMS: To investigate radiology staff perceptions of an AI tool for chest radiography triage, flagging findings suspicious for lung cancer to expedite same-day CT chest examination studies.
AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.
European radiology
Sep 20, 2024
OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and planning treatment for patients with low back pain and neurogenic pain. However, manual assessment methods are time-consuming, variable, and require axia...
Comparison between artificial intelligence solution and radiologist for the detection of pelvic, hip and extremity fractures on radiographs in adult using CT as standard of reference.
Diagnostic and interventional imaging
Sep 19, 2024
PURPOSE: The purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radi...
Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Sep 16, 2024
(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Resonance Angiography (MRA) is frequently used for the screening of UIAs due to its high resolution in ...
AI implementation: Radiologists' perspectives on AI-enabled opportunistic CT screening.
Clinical imaging
Sep 10, 2024
OBJECTIVE: AI adoption requires perceived value by end-users. AI-enabled opportunistic CT screening (OS) detects incidental clinically meaningful imaging risk markers on CT for potential preventative health benefit. This investigation assesses radiol...
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