V. Carlota Andreu‐Arasa

Author

Also Known As

Andreu-Arasa, V. Carlota, V Carlota Andreu-Arasa, V. Carlota Andreu-Arasa, V. Carlota Andreu‐Arasa, V.C. Andreu-Arasa, Vanesa Carlota Andreu Arasa, Vanesa Carlota Andreu-Arasa

Publications

558

Citations

H-Index

Concepts

All Affiliations

Boston Medical Center Boston University Hokkaido University Kagoshima University

About

V. Carlota Andreu‐Arasa is an author at Boston Medical Center specializing in radiology, medical imaging, and deep learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	4	4	120
2	Medicine	4	4	65
3	Health Sciences	3	3	120
4	Neurology	1	1	19
5	Orthopaedics	1	1	37

V. Carlota Andreu‐Arasa

Publications

411

Citations

H-Index

Page 1

	Year	Citations
AI-based differential diagnosis of dementia etiologies on multimodal data Chonghua Xue, Sahana S Kowshik, Diala Lteif, Nature Medicine	2024	121
CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy Hirofumi Kuno, Muhammad M. Qureshi, Margaret N. Chapman, American Journal of Neuroradiology	2017	81
Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma Noriyuki Fujima, V. Carlota Andreu‐Arasa, Sara K. Meibom, European Radiology Treatment OutcomeConvolutional Neural NetworkEngineeringMachine LearningMedical Imaging	2020	47
Utility of deep learning for the diagnosis of otosclerosis on temporal bone CT Noriyuki Fujima, V. Carlota Andreu‐Arasa, Keita Onoue, European Radiology Convolutional Neural NetworkEngineeringMachine LearningMedical ImagingMedical Image Computing	2021	37
Using CT texture analysis to differentiate cystic and cystic-appearing odontogenic lesions Masafumi Oda, Pedro V. Staziaki, Muhammad M. Qureshi, European Journal of Radiology Ct Texture AnalysisMedical ImagingDermatologyCystic-appearing Odontogenic LesionsCytopathology	2019	36
Prediction of the local treatment outcome in patients with oropharyngeal squamous cell carcinoma using deep learning analysis of pretreatment FDG-PET images Noriyuki Fujima, V. Carlota Andreu‐Arasa, Sara K. Meibom, BMC Cancer	2021	24
Prediction of the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma by FDG-PET imaging dataset using deep learning analysis: A hypothesis-generating study Noriyuki Fujima, V. Carlota Andreu‐Arasa, Sara K. Meibom, European Journal of Radiology Image AnalysisMachine LearningMedical ImagingHuman Papillomavirus StatusEngineering	2020	22
Amyloidosis in the head and neck: CT findings with clinicopathological correlation Koji Takumi, Pedro V. Staziaki, Rania Hito, European Journal of Radiology Ct FindingsAlzheimer's DiseaseNeck PathologyNeurologyBrain Lesion	2020	19
Cystic cervical lymph nodes of papillary thyroid carcinoma, tuberculosis and human papillomavirus positive oropharyngeal squamous cell carcinoma: utility of deep learning in their differentiation on CT Keita Onoue, Noriyuki Fujima, V. Carlota Andreu‐Arasa, American Journal of Otolaryngology EngineeringCervical CancerMedical ImagingMedicineMedical Image Computing	2021	14
Cystic cervical lymph nodes of papillary thyroid carcinoma, tuberculosis and human papillomavirus positive oropharyngeal squamous cell carcinoma: Comparative CT analysis for their differentiation Keita Onoue, Noriyuki Fujima, V. Carlota Andreu‐Arasa, European Journal of Radiology Comparative Ct AnalysisCervical CancerMedicineNasopharyngeal CancerPathology	2020	10

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