A5004851252- Natural Language Processing Techniques
- Artificial Intelligence in Healthcare and Education
- Topic Modeling
- Ethics and Social Impacts of AI
- Social Media in Health Education
- Explainable Artificial Intelligence (XAI)
- Misinformation and Its Impacts
- Text Readability and Simplification
- Public Relations and Crisis Communication
- Heart Rate Variability and Autonomic Control
- Traffic and Road Safety
- Innovative Teaching Methods
- Bioinformatics and Genomic Networks
- Viral Infections and Outbreaks Research
- Video Surveillance and Tracking Methods
- Complex Network Analysis Techniques
- Health Literacy and Information Accessibility
- Pain Mechanisms and Treatments
- Cardiovascular Syncope and Autonomic Disorders
- Rabies epidemiology and control
- Streptococcal Infections and Treatments
- Innovations in Medical Education
- Advanced Graph Neural Networks
- Autonomous Vehicle Technology and Safety
- Problem and Project Based Learning
Lakehead University
2022-2024
Defence Research and Development Organisation
2024
Amrita Vishwa Vidyapeetham
2023
New York University
2022-2023
Delhi Technological University
2020
Tribhuvan University Teaching Hospital
2018
Background The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role artificial intelligence (AI) and machine learning in this process both significant inevitable. This development raises numerous ethical concerns. study explored AI context on platforms (SMPs). It critically examined these technologies from perspectives fairness, accountability, transparency, ethics (FATE), emphasizing computational methodological...
Social media platforms (SMPs) are frequently used by various pharmaceutical companies, public health agencies, and nongovernment organizations (NGOs) for communicating concerns, new advancements, potential outbreaks. Although the benefits of using them as a tool have been extensively discussed, online activity care on SMPs during COVID-19 in terms engagement sentiment forecasting has not thoroughly investigated.The purpose this research is to analyze nature information shared Twitter,...
Background: Around 34.6% of Indian population consumes tobacco. The tobacco consumption is higher in some vulnerable such as drivers, daily wage laborers, and policemen. Tobacco known to cause oral cancers, screening for cancer these individuals reduce mortality from cancer. study was designed assess the determinants use prevalence precancerous lesions auto-rickshaw drivers.Methods: This a cross-sectional among drivers at Bareilly (UP). A total 450 were enrolled study, which 225 interviewed...
Seunggun Lee, Alexandra DeLucia, Nikita Nangia, Praneeth Ganedi, Ryan Guan, Rubing Li, Britney Ngaw, Aditya Singhal, Shalaka Vaidya, Zijun Yuan, Lining Zhang, João Sedoc. Findings of the Association for Computational Linguistics: ACL 2023.
The use of Twitter by healthcare organizations is an effective means disseminating medical information to the public. However, content tweets can be influenced various factors, such as health emergencies and breakthroughs. In this study, we conducted a discourse analysis better understand how public private factors that influence their tweets. Data were collected from accounts five pharmaceutical companies, two US Canadian agencies, World Health Organization 1 January 2020, 31 December 2022....
Introduction: Traditional methods of teaching residents in medicine are lectures, symposiums, case presentations and CMEs. Students have different levels attitude about learning responses to specific environments. A sound understanding the changing trends medical education is crucial accurate implementation adequate training protocols which helps good perception subject by students. Novel ideas concepts must pave way for modern methodologies teaching. Methodology: We administered peer...
Pretrained language models have shown success in various areas of natural processing, including reading comprehension tasks.However, when applying machine learning methods to new domains, labeled data may not always be available.To address this, we use supervised pretraining on source-domain reduce sample complexity domainspecific downstream tasks.We evaluate zeroshot performance domain-specific tasks by combining task transfer with domain adaptation fine-tune a pretrained model no labelled...
Abstract Introduction: Subclinical Autonomic Neuropathy is found in association with distal symmetric polyneuropathy diabetic patients. The Aim of this study was to compare the Cardiac Function Test parameters Type 2 Diabetes Mellitus patients and without Distal Peripheral Neuropathy. Primary Objective mean Valsalva ratio secondary find correlation between Michigan Neuropathic Screening Instrument Score test type Methods: This a single centre, cross sectional conducted from July 2022 Feb...
Computing the probability of an edge's existence in a graph network is known as link prediction. While traditional methods calculate similarity between two given nodes static network, recent research has focused on evaluating networks that evolve dynamically. Although deep learning techniques and representation algorithms, such node2vec, show remarkable improvements prediction accuracy, Stochastic Gradient Descent (SGD) method node2vec tends to fall into mediocre local optimum value due...
We address the problem of accurately predicting trajectories pedestrians in crowded scenes. Mapping and plotting human are well-known key problems autonomous systems, goal which is to enable self-driving cars explore a new environment autonomously. Extending classical RNN (recurrent neural networks) LSTM (long short-term memory) based models, we propose this work learning-based approach for error reduction accuracy improvement by utilizing visualizations Our method works effectively with...
Objectives: The objective of this study was to assess the knowledge, attitude, and practice (KAP) young doctors on rabies prophylaxis determine impact interactive lecture KAP doctors. Methods: After formulation questionnaire, review by faculty Medical Education, access web link questionnaire shared in What’sApp with all hospital. collecting pretest data, an delivered, after lecture, same again shared, responses were collected analyzed. Results: All who participated acquired good prophylaxis,...
<sec> <title>BACKGROUND</title> The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role artificial intelligence (AI) and machine learning in this process both significant inevitable. This development raises numerous ethical concerns. study explored AI context on platforms (SMPs). It critically examined these technologies from perspectives fairness, accountability, transparency, ethics (FATE), emphasizing computational...
Pretrained language models have shown success in various areas of natural processing, including reading comprehension tasks. However, when applying machine learning methods to new domains, labeled data may not always be available. To address this, we use supervised pretraining on source-domain reduce sample complexity domain-specific downstream We evaluate zero-shot performance tasks by combining task transfer with domain adaptation fine-tune a pretrained model no labelled from the target...