Co-Authors
This is a "connection" page, showing publications co-authored by Luca Saba and Jasjit Suri.
Connection Strength
13.448
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Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs. Int J Comput Assist Radiol Surg. 2021 Mar; 16(3):423-434.
Score: 0.927
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Wilson's disease: A new perspective review on its genetics, diagnosis and treatment. Front Biosci (Elite Ed). 2019 06 01; 11(1):166-185.
Score: 0.826
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The present and future of deep learning in radiology. Eur J Radiol. 2019 May; 114:14-24.
Score: 0.811
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Intra- and inter-operator reproducibility of automated cloud-based carotid lumen diameter ultrasound measurement. Indian Heart J. 2018 Sep - Oct; 70(5):649-664.
Score: 0.753
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Web-based accurate measurements of carotid lumen diameter and stenosis severity: An ultrasound-based clinical tool for stroke risk assessment during multicenter clinical trials. Comput Biol Med. 2017 12 01; 91:306-317.
Score: 0.739
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Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm. J Med Syst. 2017 Jun; 41(6):98.
Score: 0.716
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Volumetric Analysis of Carotid Plaque Components and Cerebral Microbleeds: A Correlative Study. J Stroke Cerebrovasc Dis. 2017 Mar; 26(3):552-558.
Score: 0.700
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Systematic Review of Artificial Intelligence in Acute Respiratory Distress Syndrome for COVID-19 Lung Patients: A Biomedical Imaging Perspective. IEEE J Biomed Health Inform. 2021 11; 25(11):4128-4139.
Score: 0.244
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COVLIAS 1.0: Lung Segmentation in COVID-19 Computed Tomography Scans Using Hybrid Deep Learning Artificial Intelligence Models. Diagnostics (Basel). 2021 Aug 04; 11(8).
Score: 0.240
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Complications in COVID-19 patients: Characteristics of pulmonary embolism. Clin Imaging. 2021 Sep; 77:244-249.
Score: 0.236
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Computed tomography findings of COVID-19 pneumonia in Intensive Care Unit-patients. J Public Health Res. 2021 Apr 19; 10(3).
Score: 0.235
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Bidirectional link between diabetes mellitus and coronavirus disease 2019 leading to cardiovascular disease: A narrative review. World J Diabetes. 2021 Mar 15; 12(3):215-237.
Score: 0.234
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A Novel Block Imaging Technique Using Nine Artificial Intelligence Models for COVID-19 Disease Classification, Characterization and Severity Measurement in Lung Computed Tomography Scans on an Italian Cohort. J Med Syst. 2021 Jan 26; 45(3):28.
Score: 0.232
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A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence. Comput Biol Med. 2021 03; 130:104210.
Score: 0.231
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Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence. Rev Cardiovasc Med. 2020 12 30; 21(4):541-560.
Score: 0.230
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Imaging in COVID-19-related myocardial injury. Int J Cardiovasc Imaging. 2021 Apr; 37(4):1349-1360.
Score: 0.229
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COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review. Comput Biol Med. 2020 09; 124:103960.
Score: 0.224
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Carotid artery imaging: The study of intra-plaque vascularization and hemorrhage in the era of the "vulnerable" plaque. J Neuroradiol. 2020 Nov; 47(6):464-472.
Score: 0.204
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Immunotherapy Associated Pulmonary Toxicity: Biology Behind Clinical and Radiological Features. Cancers (Basel). 2019 Mar 05; 11(3).
Score: 0.203
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Does the clinical information play a role in the magnetic resonance diagnostic confidence analysis of ovarian and deep endometriosis? Br J Radiol. 2019 Apr; 92(1096):20180548.
Score: 0.203
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A Review on a Deep Learning Perspective in Brain Cancer Classification. Cancers (Basel). 2019 01 18; 11(1).
Score: 0.201
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Nonlinear model for the carotid artery disease 10-year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: A Japanese diabetes cohort study. Echocardiography. 2019 02; 36(2):345-361.
Score: 0.201
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State-of-the-art review on deep learning in medical imaging. Front Biosci (Landmark Ed). 2019 01 01; 24(3):392-426.
Score: 0.201
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Variation of degree of stenosis quantification using different energy level with dual energy CT scanner. Neuroradiology. 2019 Mar; 61(3):285-291.
Score: 0.200
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Cerebral Small Vessel Disease: A Review Focusing on Pathophysiology, Biomarkers, and Machine Learning Strategies. J Stroke. 2018 Sep; 20(3):302-320.
Score: 0.197
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Deep learning fully convolution network for lumen characterization in diabetic patients using carotid ultrasound: a tool for stroke risk. Med Biol Eng Comput. 2019 Feb; 57(2):543-564.
Score: 0.197
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Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review. Comput Biol Med. 2018 10 01; 101:184-198.
Score: 0.196
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Echolucency-based phenotype in carotid atherosclerosis disease for risk stratification of diabetes patients. Diabetes Res Clin Pract. 2018 Sep; 143:322-331.
Score: 0.195
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Volumetric Distribution of the White Matter Hyper-Intensities in Subject with Mild to Severe Carotid Artery Stenosis: Does the Side Play a Role? J Stroke Cerebrovasc Dis. 2018 Aug; 27(8):2059-2066.
Score: 0.192
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A Survey on Coronary Atherosclerotic Plaque Tissue Characterization in Intravascular Optical Coherence Tomography. Curr Atheroscler Rep. 2018 05 21; 20(7):33.
Score: 0.192
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Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort. Comput Biol Med. 2018 07 01; 98:100-117.
Score: 0.192
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Resting-state functional connectivity MRI analysis in Human Immunodeficiency Virus and Hepatitis C Virus co-infected subjects. A pilot study. Eur J Radiol. 2018 May; 102:220-227.
Score: 0.190
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Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm. Comput Methods Programs Biomed. 2018 03; 155:165-177.
Score: 0.187
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Author Correction to: Extreme Learning Machine Framework for Risk Stratification of Fatty Liver Disease Using Ultrasound Tissue Characterization. J Med Syst. 2017 12 07; 42(1):18.
Score: 0.186
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CT Attenuation Analysis of Carotid Intraplaque Hemorrhage. AJNR Am J Neuroradiol. 2018 Jan; 39(1):131-137.
Score: 0.186
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Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm. Comput Biol Med. 2017 12 01; 91:198-212.
Score: 0.185
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Radiation dose and image quality of computed tomography of the supra-aortic arteries: A comparison between single-source and dual-source CT Scanners. J Neuroradiol. 2018 Mar; 45(2):136-141.
Score: 0.184
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Extreme Learning Machine Framework for Risk Stratification of Fatty Liver Disease Using Ultrasound Tissue Characterization. J Med Syst. 2017 08 23; 41(10):152.
Score: 0.183
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Lung disease stratification using amalgamation of Riesz and Gabor transforms in machine learning framework. Comput Biol Med. 2017 10 01; 89:197-211.
Score: 0.182
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Relationship between Automated Coronary Calcium Volumes and a Set of Manual Coronary Lumen Volume, Vessel Volume and Atheroma Volume in Japanese Diabetic Cohort. J Clin Diagn Res. 2017 Jun; 11(6):TC09-TC14.
Score: 0.180
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Extracranial internal carotid artery calcium volume measurement using computer tomography. Int Angiol. 2017 Oct; 36(5):445-461.
Score: 0.179
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Relationship between Carotid Computed Tomography Dual-Energy and Brain Leukoaraiosis. J Stroke Cerebrovasc Dis. 2017 Aug; 26(8):1824-1830.
Score: 0.179
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Relationship between white matter hyperintensities volume and the circle of Willis configurations in patients with carotid artery pathology. Eur J Radiol. 2017 04; 89:111-116.
Score: 0.176
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Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners: Stroke risk assessment. Comput Methods Programs Biomed. 2017 Apr; 141:73-81.
Score: 0.175
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Ankle-brachial index and its link to automated carotid ultrasound measurement of intima-media thickness variability in 500 Japanese coronary artery disease patients. Curr Atheroscler Rep. 2014 Mar; 16(3):393.
Score: 0.143
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Association of automated carotid IMT measurement and HbA1c in Japanese patients with coronary artery disease. Diabetes Res Clin Pract. 2013 Jun; 100(3):348-53.
Score: 0.135
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Automated carotid IMT measurement and its validation in low contrast ultrasound database of 885 patient Indian population epidemiological study: results of AtheroEdge™ Software. Int Angiol. 2012 Feb; 31(1):42-53.
Score: 0.124
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Morphologic TPA (mTPA) and composite risk score for moderate carotid atherosclerotic plaque is strongly associated with HbA1c in diabetes cohort. Comput Biol Med. 2018 10 01; 101:128-145.
Score: 0.049
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Well-balanced system for coronary calcium detection and volume measurement in a low resolution intravascular ultrasound videos. Comput Biol Med. 2017 05 01; 84:168-181.
Score: 0.044