Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Sakyajit Bhattacharya"'
Autor:
Vijay Huddar, Bapu Koundinya Desiraju, Vaibhav Rajan, Sakyajit Bhattacharya, Shourya Roy, Chandan K. Reddy
Publikováno v:
IEEE Access, Vol 4, Pp 7988-8001 (2016)
Patients in hospitals, particularly in critical care, are susceptible to many complications affecting morbidity and mortality. Digitized clinical data in electronic medical records can be effectively used to develop machine learning models to identif
Externí odkaz:
https://doaj.org/article/5f5507d9bdb540898e18a182b62c55fc
Publikováno v:
PLoS ONE, Vol 13, Iss 2, p e0193259 (2018)
An Acute Hypotensive Episode (AHE) is the sudden onset of a sustained period of low blood pressure and is one among the most critical conditions in Intensive Care Units (ICU). Without timely medical care, it can lead to an irreversible organ damage a
Externí odkaz:
https://doaj.org/article/08767761ef894203ad4a4b1ae0bb92d3
Autor:
Oishee Mazumder, Rohan Banerjee, Dibyendu Roy, Sakyajit Bhattacharya, Avik Ghose, Aniruddha Sinha
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 26:2136-2146
This paper presents a novel approach of generating synthetic Photoplethysmogram (PPG) data using a physical model of the cardiovascular system to improve classifier performance with a combination of synthetic and real data. The physical model is an i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::223b244f791cf65a8fbeb10bead70481
https://doi.org/10.1109/jbhi.2022.3147383
https://doi.org/10.1109/jbhi.2022.3147383
Autor:
Varsha Sharma, Shivam Singhal, Avik Ghose, Sakyajit Bhattacharya, Nasimuddin Ahmed, Aniruddha Sinha
Publikováno v:
ICASSP
Freezing of Gait (FoG) is a paroxysmal and devitalizing symptom associated with Parkinson’s disease (PD). Episodes of FoG impedes gait and augments fall propensity, often leading to serious fall-injury. In this paper, we present a method for online
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22090480ee134f3aa161bff23325a0d7
https://doi.org/10.1109/icassp39728.2021.9414780
https://doi.org/10.1109/icassp39728.2021.9414780
Publikováno v:
ICASSP
Synthetic data generation has recently emerged as a substitution technique for handling the problem of bulk data needed in training machine learning algorithms. Healthcare, primarily cardiovascular domain is a major area where synthetic physiological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aad96da9aa95026e1836a00d35f4e0af
https://doi.org/10.1109/icassp40776.2020.9054570
https://doi.org/10.1109/icassp40776.2020.9054570
Publikováno v:
EMBC
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Synthetic data generation has recently emerged as a substitution technique for handling the problem of bulk data needed in training machine learning algorithms. Healthcare, primarily cardiovascular domain is a major area where synthetic physiological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e08ace38bad3e24ca20c8c855d885383
https://pubmed.ncbi.nlm.nih.gov/31946988
https://pubmed.ncbi.nlm.nih.gov/31946988
Publikováno v:
EMBC
Aging in place and independent living for the elderly has gained importance, and so has instrumented homes for ambient assisted living (AAL). In this paper we explore the feasibility of using passive sensors to provide insights into the cognitive and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1037b326e4920b875f245a6b56138a2
https://doi.org/10.1109/embc.2019.8856435
https://doi.org/10.1109/embc.2019.8856435
Autor:
Vaibhav Rajan, Vijay Huddar, Sakyajit Bhattacharya, Shourya Roy, Bapu Koundinya Desiraju, Chandan K. Reddy
Publikováno v:
IEEE Access, Vol 4, Pp 7988-8001 (2016)
Patients in hospitals, particularly in critical care, are susceptible to many complications affecting morbidity and mortality. Digitized clinical data in electronic medical records can be effectively used to develop machine learning models to identif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1420835bd24e4546a9b850346619dab
https://ieeexplore.ieee.org/document/7593335/
https://ieeexplore.ieee.org/document/7593335/
Publikováno v:
Bioinformatics (Oxford, England). 36(2)
Motivation The identification of sub-populations of patients with similar characteristics, called patient subtyping, is important for realizing the goals of precision medicine. Accurate subtyping is crucial for tailoring therapeutic strategies that c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9fe6d2739e340ff11d3901413e27695
https://pubmed.ncbi.nlm.nih.gov/31368480
https://pubmed.ncbi.nlm.nih.gov/31368480
Publikováno v:
CBMS
In this paper we propose a novel process flow of a low-cost, non-invasive screening system for identifying Coronary Artery Disease (CAD) patients using a two-stage classification approach. A statistical rule engine is designed based on patient demogr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c8df5d03fbeaad40370d63dbba30411
https://doi.org/10.1109/cbms.2018.00043
https://doi.org/10.1109/cbms.2018.00043