Research Portfolio - Nikhil G. Thaker, MD

Research Overview

My research focuses on the intersection of artificial intelligence, healthcare informatics, and radiation oncology. I lead innovative projects that leverage cutting-edge technology to improve cancer care delivery, enhance clinical decision-making, and advance precision medicine approaches.

Our team collaborates with leading institutions and industry partners to develop AI-powered solutions that address real-world clinical challenges. From large language models for radiation oncology to computer vision for cancer detection, we're pushing the boundaries of what's possible in healthcare technology.

Current research areas include:

AI and Machine Learning in Radiation Oncology
Clinical Decision Support Systems
Healthcare Data Interoperability
Digital Health for Underserved Communities
Predictive Analytics for Treatment Outcomes

View Selected Publications

Current Research Projects

RadOncRAG - Large Language Model for Radiation Oncology

Developing a specialized large language model trained on radiation oncology literature and clinical guidelines to assist physicians in treatment planning and decision-making.

Python TensorFlow NLP Clinical Data

AI-Powered Computer Vision for Cancer Detection

Implementing deep learning algorithms for automated detection and classification of cancer in medical imaging, with focus on improving early detection rates.

Computer Vision PyTorch Medical Imaging Deep Learning

Clinical Decision Support System

Building an intelligent system that integrates patient data, clinical guidelines, and real-time analytics to provide evidence-based treatment recommendations.

Machine Learning EHR Integration Clinical Guidelines Real-time Analytics

Digital Health Platform for Underserved Communities

Developing a comprehensive digital health platform to improve access to cancer care for underserved populations through telemedicine and remote monitoring.

Telemedicine Mobile Health Remote Monitoring Health Equity

Predictive Analytics for Treatment Outcomes

Creating predictive models to forecast patient outcomes and treatment responses based on clinical, genomic, and demographic data.

Predictive Modeling Genomics Statistical Analysis Clinical Data

Automated Treatment Planning System

Developing AI-driven algorithms to automate and optimize radiation therapy treatment planning, reducing planning time while maintaining quality.

Treatment Planning Optimization Radiation Therapy Automation

Healthcare Data Interoperability Platform

Creating a unified platform for seamless data exchange between different healthcare systems and applications, improving care coordination and patient outcomes.

Interoperability HL7 FHIR API Development Data Standards

Real-time Clinical Analytics Dashboard

Building a comprehensive analytics platform that provides real-time insights into clinical performance, patient outcomes, and operational efficiency.

Real-time Analytics Data Visualization Business Intelligence Performance Metrics

Join Our Research Team

We're always looking for talented individuals who are passionate about healthcare technology and innovation. Our team includes physicians, researchers, engineers, and students working together to advance the field of AI in healthcare.

Current Opportunities

Research Fellows

Join our team as a research fellow and contribute to cutting-edge AI projects in healthcare. Ideal for recent graduates or professionals looking to transition into healthcare technology.

Clinical Collaborators

Physicians and healthcare professionals interested in implementing AI solutions in their practice. We provide training and support for clinical integration.

Student Internships

Undergraduate and graduate students can gain hands-on experience in healthcare AI through our internship program. Projects range from data analysis to algorithm development.

Contact Us

Interested in collaborating or joining our research team? Contact us to learn more about current opportunities and how you can contribute to our mission of advancing healthcare through technology.

Contact Research Team