Clinical Radiology

Papers
(The H4-Index of Clinical Radiology is 22. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Utilisation of deep learning for COVID-19 diagnosis67
The future of CT: deep learning reconstruction59
A meta-analysis comparing the diagnostic performance of abbreviated MRI and a full diagnostic protocol in breast cancer44
COVID-19-related intracranial imaging findings: a large single-centre experience44
Introduction to radiomics for a clinical audience42
Use of Hologic LOCalizer radiofrequency identification (RFID) tags to localise impalpable breast lesions and axillary nodes: experience of the first 150 cases in a UK breast unit38
Imaging of the temporomandibular joint37
Postoperative complications of colorectal cancer35
Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma35
The potential utility of abbreviated breast MRI (FAST MRI) as a tool for breast cancer screening: a systematic review and meta-analysis31
Artificial intelligence in radiology: relevance of collaborative work between radiologists and engineers for building a multidisciplinary team29
Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma29
Leadership for continuous improvement in healthcare during the time of COVID-1929
Fluorine-18 labelled prostate-specific membrane antigen (PSMA)-1007 positron-emission tomography–computed tomography: normal patterns, pearls, and pitfalls28
Initial chest radiograph scores inform COVID-19 status, intensive care unit admission and need for mechanical ventilation25
Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance25
Morton's neuroma: review of anatomy, pathomechanism, and imaging25
Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels24
Imaging findings using a combined MRI/CT protocol to identify the “entire iceberg” in post-COVID-19 mucormycosis presenting clinically as only “the tip”24
Diagnosis of normal chest radiographs using an autonomous deep-learning algorithm23
Thermography in rheumatoid arthritis: a comparison with ultrasonography and clinical joint assessment22
Imaging of COVID-19-associated craniofacial mucormycosis: a black and white review of the “black fungus”22
Challenges and opportunities for artificial intelligence in oncological imaging22
Radiomics-based machine-learning method for prediction of distant metastasis from soft-tissue sarcomas22
The image quality of deep-learning image reconstruction of chest CT images on a mediastinal window setting22
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