About Aftab Tariq
Aftab Tariq is a healthcare researcher specializing in AI-driven solutions for early disease detection. With over 5 years of IT experience, he leads groundbreaking research in cardiovascular health at American National University, utilizing machine learning to enhance diagnostic accuracy. His work bridges the gap between technology and healthcare, contributing to improved patient outcomes.
Research Focus and Contributions
Aftab Tariq specializes in developing advanced AI models for early disease detection and diagnosis. His work focuses on leveraging machine learning techniques to enhance predictive accuracy and patient outcomes. Notable contributions include innovative algorithms that have significantly improved diagnostic efficiency and precision in various medical conditions.
Achievements
- Development of Advanced AI-Driven Models for Disease Detection
- Published Research in Leading Journals
- Speaker at Prestigious Conferences
- Collaborative Research Grants
- Patents for Innovative Techniques
- Mentorship and Training
- Development of Clinical Partnerships
- Recognition from Professional Associations
- Innovation in Healthcare Technology
My Journey as a ReSEARCHER
Research Area
- Spearheaded AI-based research for early cardiovascular disease detection at American National University.
- Published multiple papers on AI in healthcare, cited extensively in reputable journals.
- Secured research grants for groundbreaking healthcare AI projects.
- Played a pivotal role in the development of high-performance Android applications in collaboration with cross-functional teams.
Research
- AI in Cardiovascular Healthcare: Developed machine learning models to enhance early-stage heart disease detection.
- Equity in Surgical Care: Explored AI’s role in promoting fairness and reducing bias in surgical procedures.
- AI in Orthopedic Surgery: Investigated AI applications for improving value-based healthcare delivery in orthopedic surgery.
Projects
- OffRoad Adventures (Android App): A community-based trip recommendation system designed to enhance user experiences through collaboration.
- Shopping Assistant (Location-based System): Integrated Google Maps API to provide tailored recommendations for nearby stores and services.
Publications Record
Role of AI in Cardiovascular Health Care: A Brief Overview
Evaluating the Potential of Artificial Intelligence in Orthopedic Surgery for Value-Based Healthcare
Equity and Artificial Intelligence in Surgical Care: A Comprehensive Review
Journal of World Science, Vol. 2 No. 4 (2023)
A comprehensive study on AI's role in cardiovascular care, focusing on improving diagnostic accuracy using machine learning algorithms.
Cited by: 15
Equity and Artificial Intelligence in Surgical Care: A Comprehensive Review
Evaluating the Potential of Artificial Intelligence in Orthopedic Surgery for Value-Based Healthcare
Equity and Artificial Intelligence in Surgical Care: A Comprehensive Review
BULLET: Journal Multidiscipline Ilmu, Vol. 2 No. 2 (2023)
This paper explores AI's potential in reducing biases and improving equity in surgical care.
Cited by: 18
Evaluating the Potential of Artificial Intelligence in Orthopedic Surgery for Value-Based Healthcare
Evaluating the Potential of Artificial Intelligence in Orthopedic Surgery for Value-Based Healthcare
Evaluating the Potential of Artificial Intelligence in Orthopedic Surgery for Value-Based Healthcare
International Journal of Multidisciplinary Sciences and Arts, Vol. 2 No. 1 (2023)
A look at how AI can revolutionize orthopedic surgery through enhanced planning, diagnostics, and patient care.
Cited by: 48
Principles and Perspectives in Medical Diagnostic Systems Employing AI Algorithms
Maximizing Efficiency in Telemedicine: An IoT-Based AI Optimization Framework for Health Analysis
Evaluating the Potential of Artificial Intelligence in Orthopedic Surgery for Value-Based Healthcare
International Research Journal of Economics and Management Studies, Vol. 3 (2023)
This paper categorizes AI methods for disease diagnosis and highlights applications in various illnesses.
Cited by: 29
A Review of Biosensors and Artificial Intelligence in Healthcare and Their Clinical Significance
Maximizing Efficiency in Telemedicine: An IoT-Based AI Optimization Framework for Health Analysis
Maximizing Efficiency in Telemedicine: An IoT-Based AI Optimization Framework for Health Analysis
International Research Journal of Economics and Management Studies, Vol. 3 (2024)
This review covers advancements in AI and biosensors in healthcare, emphasizing personalized medicine.
Cited by: 29
Maximizing Efficiency in Telemedicine: An IoT-Based AI Optimization Framework for Health Analysis
Maximizing Efficiency in Telemedicine: An IoT-Based AI Optimization Framework for Health Analysis
Maximizing Efficiency in Telemedicine: An IoT-Based AI Optimization Framework for Health Analysis
European Journal of Science Innovation and Technology, Vol. 3 (2023)
Introduces a framework using AI and IoT to improve telemedicine services and health analysis.
Cited by: 15
A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilit
A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilit
A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilit
European Journal of Science Innovation and Technology, Vol. 3 (2023)
AI-driven system that adapts educational content for intellectually disabled students based on emotional states.
Cited by: 12
Deep Dive into Health: Harnessing AI and Deep Learning for Brain and Heart Care
A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilit
A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilit
International Journal of Advanced Engineering Technologies and Innovations, Vol. 5 No. 2 (2023)
Discusses the potential of AI and deep learning in diagnosing and managing neurological and cardiovascular diseases.
Cited by: 13
A Novel Deep Learning Approach for the Detection of Cardiovascular Disease Using Sentiment Analysis
A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilit
A Novel Deep Learning Approach for the Detection of Cardiovascular Disease Using Sentiment Analysis
European Journal of Biomedical Sciences, 2023
Proposes a deep learning model using sentiment analysis for more accurate detection of cardiovascular diseases.
The Smart Early Prediction of Congenital Heart Disease in Pregnancy Using a Deep Learning Model
Revolutionizing Healthcare: How Deep Learning is Poised to Change the Landscape of Medical Diagnosis
A Novel Deep Learning Approach for the Detection of Cardiovascular Disease Using Sentiment Analysis
STPEC Conference, 2023
Focuses on early prediction models for congenital heart defects in pregnant women, achieving high prediction accuracy using deep learning techniques.
Revolutionizing Healthcare: How Deep Learning is Poised to Change the Landscape of Medical Diagnosis
Revolutionizing Healthcare: How Deep Learning is Poised to Change the Landscape of Medical Diagnosis
Revolutionizing Healthcare: How Deep Learning is Poised to Change the Landscape of Medical Diagnosis
European Journal of Science Innovation and Technology, Vol. 5 No. 2 (2023)
Explores the potential of deep learning in transforming healthcare diagnostics, personalized medicine, and ethical considerations.
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Aftab Tariq
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