Shyam Visweswaran
Overview
Explore the profile of Shyam Visweswaran including associated specialties, affiliations and a list of published articles.
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Articles
156
Citations
1955
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Recent Articles
1.
Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant
Chaudhary R, Nourelahi M, Thoma F, Gellad W, Lo-Ciganic W, Chaudhary R, et al.
Am J Cardiol
. 2025 Feb;
PMID: 40015543
Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alternatives like left atrial appendage closure devices lower stroke risk with...
2.
Al-Qudah A, Alkalbani L, Tallapaneni P, Vinuthna D, Suresh V, Anetakis K, et al.
Eur Neurol
. 2025 Feb;
:1-17.
PMID: 39999825
Introduction: Postoperative delirium (POD) that is associated with intracranial surgeries can have several adverse outcomes, including a high rate of morbidity and mortality. The use of intraoperative neurophysiological monitoring (IONM)...
3.
DiSanto D, Tang W, Zhu W, Morris M, Visweswaran S, Cai T, et al.
medRxiv
. 2025 Feb;
PMID: 39974119
Background: B-cell depletion (BCD) therapies ( ocrelizumab, ofatumumab, rituximab) and natalizumab (NTZ) are highly effective disease-modifying therapies (DMTs) for multiple sclerosis (MS). However, no randomized clinical trial and only limited...
4.
Wang Y, Hilsman J, Li C, Morris M, Heider P, Fu S, et al.
medRxiv
. 2025 Feb;
PMID: 39974073
Electronic health record (EHR) data are a rich and invaluable source of real-world clinical information, enabling detailed insights into patient populations, treatment outcomes, and healthcare practices. The availability of large...
5.
Bhavnani S, Zhang W, Bao D, Raji M, Ajewole V, Hunter R, et al.
J Med Internet Res
. 2025 Feb;
27:e48775.
PMID: 39932771
Background: Social determinants of health (SDoH), such as financial resources and housing stability, account for between 30% and 55% of people's health outcomes. While many studies have identified strong associations...
6.
Wang T, Henderson D, Weber G, Morris M, Sadhu E, Murphy S, et al.
medRxiv
. 2025 Jan;
PMID: 39867368
Objective: Federated research networks, like Evolve to Next-Gen Accrual of patients to Clinical Trials (ENACT), aim to facilitate medical research by exchanging electronic health record (EHR) data. However, poor data...
7.
Wang L, Venkatesh S, Morris M, Li M, Srivastava R, Visweswaran S, et al.
medRxiv
. 2025 Jan;
PMID: 39763548
Background: People with Alzheimer's disease (AD) exhibit varying clinical trajectories. There is a need to predict future AD-related outcomes such as morbidity and mortality using clinical profile at the point...
8.
Anderson J, Visweswaran S
JAMIA Open
. 2024 Dec;
8(1):ooae149.
PMID: 39737346
Objectives: Statistical and artificial intelligence algorithms are increasingly being developed for use in healthcare. These algorithms may reflect biases that magnify disparities in clinical care, and there is a growing...
9.
Menezes M, Hoffmann A, Tan A, Nalbandyan M, Omenn G, Mazzotti D, et al.
Lancet Digit Health
. 2024 Dec;
7(1):e35-e43.
PMID: 39722251
Background: Patient notes contain substantial information but are difficult for computers to analyse due to their unstructured format. Large-language models (LLMs), such as Generative Pre-trained Transformer 4 (GPT-4), have changed...
10.
Hanna M, Hanna M, Pantanowitz L, Jackson B, Palmer O, Visweswaran S, et al.
Mod Pathol
. 2024 Dec;
38(3):100686.
PMID: 39694331
As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny. Ethics and bias are important...