Ankush D Jamthikar
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Explore the profile of Ankush D Jamthikar including associated specialties, affiliations and a list of published articles.
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22
Citations
383
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Recent Articles
1.
Hathaway Q, Jamthikar A, Rajiv N, Chaitman B, Carson J, Yanamala N, et al.
Echo Res Pract
. 2024 Sep;
11(1):22.
PMID: 39278898
Background: Current risk stratification tools for acute myocardial infarction (AMI) have limitations, particularly in predicting mortality. This study utilizes cardiac ultrasound radiomics (i.e., ultrasomics) to risk stratify AMI patients when...
2.
Konstantonis G, Singh K, Sfikakis P, Jamthikar A, Kitas G, Gupta S, et al.
Rheumatol Int
. 2022 Jan;
42(2):215-239.
PMID: 35013839
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542...
3.
Munjral S, Ahluwalia P, Jamthikar A, Puvvula A, Saba L, Faa G, et al.
Front Biosci (Landmark Ed)
. 2021 Dec;
26(11):1312-1339.
PMID: 34856770
: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often...
4.
Johri A, Mantella L, Jamthikar A, Saba L, Laird J, Suri J
Int J Cardiovasc Imaging
. 2021 May;
37(11):3145-3156.
PMID: 34050838
The aim of this study was to compare machine learning (ML) methods with conventional statistical methods to investigate the predictive ability of carotid plaque characteristics for assessing the risk of...
5.
Viswanathan V, Puvvula A, Jamthikar A, Saba L, Johri A, Kotsis V, et al.
World J Diabetes
. 2021 Mar;
12(3):215-237.
PMID: 33758644
Coronavirus disease 2019 (COVID-19) is a global pandemic where several comorbidities have been shown to have a significant effect on mortality. Patients with diabetes mellitus (DM) have a higher mortality...
6.
Suri J, Puvvula A, Majhail M, Biswas M, Jamthikar A, Saba L, et al.
Rev Cardiovasc Med
. 2021 Jan;
21(4):541-560.
PMID: 33387999
Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived...
7.
Jamthikar A, Puvvula A, Gupta D, Johri A, Nambi V, Khanna N, et al.
Int Angiol
. 2020 Nov;
40(2):150-164.
PMID: 33236868
Chronic kidney disease (CKD) and cardiovascular disease (CVD) together result in an enormous burden on global healthcare. The estimated glomerular filtration rate (eGFR) is a well-established biomarker of CKD and...
8.
Jamthikar A, Gupta D, Mantella L, Saba L, Laird J, Johri A, et al.
Int J Cardiovasc Imaging
. 2020 Nov;
37(4):1171-1187.
PMID: 33184741
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal...
9.
Jamthikar A, Gupta D, Johri A, Mantella L, Saba L, Kolluri R, et al.
J Med Syst
. 2020 Nov;
44(12):208.
PMID: 33175247
This study developed an office-based cardiovascular risk calculator using a machine learning (ML) algorithm that utilized a focused carotid ultrasound. The design of this study was divided into three steps....
10.
Jamthikar A, Gupta D, Saba L, Khanna N, Viskovic K, Mavrogeni S, et al.
Comput Biol Med
. 2020 Oct;
126:104043.
PMID: 33065389
Recent Findings: Cardiovascular disease (CVD) is the leading cause of mortality and poses challenges for healthcare providers globally. Risk-based approaches for the management of CVD are becoming popular for recommending...