A5037243800- Cardiovascular Function and Risk Factors
- Cardiac Valve Diseases and Treatments
- Cardiac Imaging and Diagnostics
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Advanced MRI Techniques and Applications
- Liver Disease and Transplantation
- Cardiomyopathy and Myosin Studies
- Gallbladder and Bile Duct Disorders
- Context-Aware Activity Recognition Systems
- Liver Disease Diagnosis and Treatment
- Bayesian Modeling and Causal Inference
- Artificial Intelligence in Healthcare
- Hepatocellular Carcinoma Treatment and Prognosis
- Cardiac Structural Anomalies and Repair
- Pancreatitis Pathology and Treatment
- IoT and Edge/Fog Computing
- Anomaly Detection Techniques and Applications
- Energy Load and Power Forecasting
- Image Enhancement Techniques
- Ultrasound and Hyperthermia Applications
- Robotics and Automated Systems
- Digital Mental Health Interventions
- Ultrasound Imaging and Elastography
- Organ Transplantation Techniques and Outcomes
- Swearing, Euphemism, Multilingualism
Northwestern University
2020-2025
Stanford University
2023-2024
Navrachana University
2023
Maharaja Sayajirao University of Baroda
2023
Institute of Transplantation Sciences
2021
Delhi Technological University
2021
Shirley Ryan AbilityLab
2016-2017
University of California, San Francisco
2015
University of Michigan
2009
The energy demand is increasing every day. This increase in has led us to find alternate sources of energy. non-renewable have limited supply, and constant use gives rise various types pollution. Gradually, people started relying on renewable due their abundance nature. Alternately, Solar Energy (SE) one the best India. paper aims predict output production Power Plants KWh. Also, this research attempts relation weather attributes with power generated. Decision Tree Regressor model will be...
Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) shows promise for quantifying mitral regurgitation (MR) by allowing direct regurgitant volume (RVol) measurement using a plane precisely placed at the MR jet. However, ideal location of remains unclear. This study aims to systematically examine how varying locations affect RVol quantification and determine optimal momentum conservation principle free Patients diagnosed with transthoracic echocardiography (TTE) scheduled CMR...
Machine learning allows detecting specific physical activities using data from wearable sensors. Such a quantification of patient mobility over time promises to accurately inform clinical decisions for rehabilitation. There are two strategies setting up the machine problem: detect one patient's same (personal model) or their other patients (global model), and we currently do not know if personal models necessary. Here consider problem waist-worn accelerometer in who use knee-ankle-foot...
Quantitative evaluation of mitral regurgitation (MR) in hypertrophic cardiomyopathy (HCM) by cardiovascular magnetic resonance (CMR) relies on an indirect volumetric calculation. The aim this study was to directly assess and quantify MR jets patients with HCM using 4D flow CMR jet tracking comparison standard-of-care method. This retrospective included undergoing CMR. By the method from CMR, volume quantified as left ventricular stroke minus forward aortic volume. direct tracking,...
Background: Wearable sensors gather data that machine-learning models can convert into an identification of physical activities, a clinically relevant outcome measure. However, when individuals with disabilities upgrade to new walking assistive device, their gait patterns change, which could affect the accuracy activity recognition.
Purpose The purpose of this study was to evaluate the accuracy four‐dimensional (4D) flow MRI for direct assessment peak velocity, volume, and momentum a mitral regurgitation (MR) jets using an in vitro pulsatile jet phantom. We systematically investigated impact spatial resolution quantification location along on quantities with Doppler ultrasound as reference velocity. Methods Four‐dimensional data through circular, elliptical, 3D‐printed patient‐specific MR orifice model acquired varying...
Depression is a typical and severe mental health condition that can have an adverse effect on person's emotions, thoughts, behaviours. Suicide result from depression. It could lead to number of physical emotional problems as well decline in your capacity for both work home life. More than 264 million people every age demographic around the world are affected by Social media post analysis will help identifying depression because younger generation more dependent it. A system identify has been...
Background MRI‐derived left atrial (LA) longitudinal strain has been shown to be a marker for mitral regurgitation, but the utility of LA circumferential remains unclear. Purpose To assess feasibility and reproducibility strain, identify changes in regurgitation patients compared healthy volunteers, determine strain's association with severity cardiac function. Study Type Retrospective. Population 52 patients, 12 volunteers. Field Strength/Sequence Steady‐state free precession cine 2D phase...
Analyzing datasets for Risky Decision Making (RDM) is a challenging task involving the identification of varied decision making patterns and categorization individuals. Researchers from various fields as diverse psychology marketing are actively working to identify suitable techniques, which will allow understanding processes better. have commonly used machine learning algorithms model processes. However, high computational costs most make such endeavors increasingly large datasets. One...
Chronic kidney disease patients on hemodialysis (CKD-5D) are among the worst hit by coronavirus 2019 (COVID-19) pandemic. Need to travel for dialysis, comorbidities, and immunosuppressive state put them at risk of severe poor outcomes. We report our experience COVID-19 in a cohort CKD-5D from public sector tertiary-care center western India.We retrospectively analyzed records 58 with confirmed admitted hospital. Suspected COVID-19, acute injury (AKI), or AKI CKD were excluded. studied...
We present an efficient anomaly detection algorithm, named BANBAD. Using belief networks (BNs), the algorithm identifies abnormal behavior, like inappropriate energy consumption, in mobile ad-hoc (MANETs). By applying structure learning techniques to training dataset, BANBAD extracts dependencies among relevant features, such as average velocity, displacement, local computation and communication time, response of a node network. A directed acyclic graph (DAG) is used represent features their...
There is increasing interest in the application of radiation segmentectomy (RS) with Yttrium-90 microspheres for treating liver cancers other than Hepatocellular Carcinoma. In this study, we aim to evaluate efficacy RS treatment early-stage intrahepatic cholangiocarcinoma (ICC). With institutional review board approval, a retrospective chart including all patients T1a (solitary tumor ≤5 cm without vascular invasion) and T1b >5 stage ICC according The American Joint Committee on Cancer (AJCC)...
Short-axis CMR left atrial (LA) circumferential strain has not yet been investigated as a cardiac biomarker. This study assessed feasibility and reproducibility of LA in healthy cohort, examined changes within mitral regurgitation (MR) patients, correlations between reproducible measures MR severity function. Reservoir globally at superior mid regions was found to be reproducible, significantly different volunteers correlated with is potential utility evaluating impaired mechanics patients.
Nowadays, herbs used worldwide due to its medicinal and pharmaceutical potentials. Herbs are also prevent human beings from variety of diseases. In the current study, alcoholic extract which is commonly known as green chiretta in development handwash (herbal). Traditionally, was for their different pharmacological action. Alcoholic loaded herbal hand wash prepared by using Carbopol-934 gelling agent, TEA (triehanolamine) neutralizer sodium lauryl sulfoacetate (SLSA) surfactant. Antibacterial...