Dan M. Popescu

646 total citations
26 papers, 405 citations indexed

About

Dan M. Popescu is a scholar working on Cardiology and Cardiovascular Medicine, Neurology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dan M. Popescu has authored 26 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cardiology and Cardiovascular Medicine, 7 papers in Neurology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dan M. Popescu's work include Cardiac Imaging and Diagnostics (4 papers), Intracranial Aneurysms: Treatment and Complications (4 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Dan M. Popescu is often cited by papers focused on Cardiac Imaging and Diagnostics (4 papers), Intracranial Aneurysms: Treatment and Complications (4 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Dan M. Popescu collaborates with scholars based in Romania, United States and Belgium. Dan M. Popescu's co-authors include Loretta Ichim, Julie K. Shade, Natalia A. Trayanova, Hugh Calkins, Adityo Prakosa, David Spragg, Mauro Maggioni, Kathérine C. Wu, Joseph E. Marine and Rheeda L. Ali and has published in prestigious journals such as SHILAP Revista de lepidopterología, Science Advances and Sensors.

In The Last Decade

Dan M. Popescu

22 papers receiving 385 citations

Peers

Countries citing papers authored by Dan M. Popescu

Since Specialization

Citations

This map shows the geographic impact of Dan M. Popescu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dan M. Popescu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan M. Popescu more than expected).

Fields of papers citing papers by Dan M. Popescu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dan M. Popescu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dan M. Popescu. The network helps show where Dan M. Popescu may publish in the future.

Co-authorship network of co-authors of Dan M. Popescu

This figure shows the co-authorship network connecting the top 25 collaborators of Dan M. Popescu. A scholar is included among the top collaborators of Dan M. Popescu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dan M. Popescu. Dan M. Popescu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Multimodal AI to forecast arrhythmic death in hypertrophic cardiomyopathy 2025 ·Nature Cardiovascular Research ·(unknown), Minglang Yin, Eugene Kholmovski, Dan M. Popescu, Dai-Yin Lu, (unknown), (unknown), Stefan L. Zimmerman, Jonathan Chrispin, Allison G. Hays, Dermot Phelan, M. Roselle Abraham, Natalia A. Trayanova	5
2	PO-05-009 COMBINED LEFT AND RIGHT ATRIAL NETWORK (CLARANET): A DEEP LEARNING (DL) MODEL FOR REPRODUCIBLE LGE-MRI AUTOMATIC SEGMENTATION OF LEFT AND RIGHT ATRIA (LA/RA) IN ATRIAL FIBRILLATION (AF) TREATMENT PLANNING 2024 ·Heart Rhythm ·Arthur H. Lefebvre, (unknown), (unknown), (unknown), (unknown), (unknown), Rheeda L. Ali, (unknown), Julie K. Shade, Dan M. Popescu, Adityo Prakosa, Eugene Kholmovski, Natalia A. Trayanova	2
3	PO-02-095 MAARS-HCM: MULTI-MODAL ARTIFICIAL INTELLIGENCE (AI) FOR VENTRICULAR ARRHYTHMIA (VA) RISK STRATIFICATION IN HYPERTROPHIC CARDIOMYOPATHY (HCM) PATIENTS 2024 ·Heart Rhythm ·(unknown), Minglang Yin, Dan M. Popescu, Dai‐Yin Lu, (unknown), M. Engels, (unknown), (unknown), Jonathan Chrispin, Dermot Phelan, M. Roselle Abraham, Allison G. Hays, Natalia A. Trayanova	1
4	LASSNet: A Four Steps Deep Neural Network for Left Atrial Segmentation and Scar Quantification 2023 ·Lecture notes in computer science ·(unknown), (unknown), Julie K. Shade, Ryan Bradley, (unknown), Rheeda L. Ali, Dan M. Popescu, Adityo Prakosa, Eugene Kholmovski, Natalia A. Trayanova	5
5	Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart 2022 ·Nature Cardiovascular Research ·Dan M. Popescu, Julie K. Shade, (unknown), Konstantinos N. Aronis, David Ouyang, M. Vinayaga Moorthy, Nancy R. Cook, Daniel Lee, Alan H. Kadish, Christine M. Albert, Kathérine C. Wu, Mauro Maggioni, Natalia A. Trayanova	58
6	Real-Time Prediction of Mortality, Cardiac Arrest, and Thromboembolic Complications in Hospitalized Patients With COVID-19 2022 ·JACC Advances ·Julie K. Shade, (unknown), Eric Sung, Dan M. Popescu, Anum Minhas, Nisha A. Gilotra, Konstantinos N. Aronis, Allison G. Hays, Natalia A. Trayanova	4
7	Predicting risk of sudden cardiac death in patients with cardiac sarcoidosis using multimodality imaging and personalized heart modeling in a multivariable classifier 2021 ·Science Advances ·Julie K. Shade, Adityo Prakosa, Dan M. Popescu, (unknown), David R. Okada, Jonathan Chrispin, Natalia A. Trayanova	49
8	Anatomically informed deep learning on contrast-enhanced cardiac magnetic resonance imaging for scar segmentation and clinical feature extraction 2021 ·SHILAP Revista de lepidopterología ·Dan M. Popescu, (unknown), (unknown), (unknown), Julie K. Shade, Kathérine C. Wu, Mauro Maggioni, Natalia A. Trayanova	26
9	Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation 2020 ·Circulation Arrhythmia and Electrophysiology ·Julie K. Shade, Rheeda L. Ali, (unknown), Dan M. Popescu, Tauseef Akhtar, Joseph E. Marine, David Spragg, Hugh Calkins, Natalia A. Trayanova	70
10	Deep Learning–Based Methods for Automatic Diagnosis of Skin Lesions 2020 ·Sensors ·(unknown), Dan M. Popescu, Loretta Ichim	106
11	Correlations between intra and extraarticular factors measured by computed tomography in patients with recurrent patellar dislocation 2020 ·(unknown), (unknown), (unknown), (unknown), Dan M. Popescu	0
12	Emotion Classification Using a Tensorflow Generative Adversarial Network Implementation 2018 ·Symmetry ·(unknown), Dan M. Popescu, Loretta Ichim	17
13	Control and Optimization of UAV Trajectory for Aerial Coverage in Photogrammetry Applications 2016 ·Advances in Electrical and Computer Engineering ·Dan M. Popescu, Florin Stoican, Loretta Ichim	3
14	A rare case of acute lymphoblastic leukemia in a patient with light chain (AL) amyloidosis treated with lenalidomide. 2014 ·PubMed ·Ranjit Nair, Shereen Gheith, Dan M. Popescu, Nicole M Agostino	3
15	Lead electrocardiogram changes after supratentorial intracerebral hemorrhage. 2012 ·PubMed ·Dan M. Popescu, (unknown), (unknown), (unknown), (unknown)	9
16	Review on the causes of trigeminal neuralgia symptomatic to other diseases 2011 ·SHILAP Revista de lepidopterología ·Florin Popovici, (unknown), Dan M. Popescu, (unknown)	3
17	Transformation of the 5q- syndrome to acute lymphoblastic leukemia: a report of two cases and review of the literature. 2011 ·PubMed ·Nicole M Agostino, (unknown), Dan M. Popescu, Shereen Gheith	11
18	Spontaneous intracranial internal carotid artery dissection 2010 ·Romanian Journal of Neurology ·(unknown), Dan M. Popescu, (unknown)	0
19	VERTEBRAL ARTERY DISSECTION – CLINICAL ASPECTS 2008 ·SHILAP Revista de lepidopterología ·(unknown), Mihaela Oana Romanitan, (unknown), Dan M. Popescu, Adina Roceanu, Cristina Tiu, Ovidiu Băjenaru	0
20	Tendencies of International Career of Romanian Researchers: Brain Drain?. 2006 ·Dan M. Popescu, (unknown), (unknown)	3

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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