Description:

• Delve into the urgent need for effective prevention, early diagnosis, and advanced treatment methods for lung cancer, a leading cause of global mortality.
• Explore the transformative potential of Large Language Models (LLMs) and Natural Language Processing (NLP) in automatic lung cancer diagnosis through a systematic review.
• Investigate LLM applications, AI-generated Next-Generation Sequencing (NGS) reports, and NLP techniques in lung cancer diagnosis, assessing achievements and challenges.
• Highlight the critical role of AI in medical imaging, improving responses to non-expert queries, refining NGS reports, and evaluating AI in lung cancer screening.
• Discuss the exploration of deep learning approaches in the field of lung cancer diagnosis.
• Provide insights into the dynamic landscape of lung cancer research and emphasize the importance of ongoing advancements in diagnostic methods.
• Serve as a roadmap for researchers, encouraging further exploration and contributions to the ongoing progress in lung cancer diagnosis and treatment.

Prerequisites:

The prerequisites for this talk include:

1. Basic understanding of lung cancer and its significance as a global health challenge.
2. Familiarity with concepts related to artificial intelligence (AI), including Large Language Models (LLMs) and Natural Language Processing (NLP).
3. General knowledge of medical imaging techniques and Next-Generation Sequencing (NGS) reports.
4. Awareness of the role of AI in healthcare and its potential applications in medical diagnosis.
5. Interest in the intersection of technology and healthcare, particularly in the context of improving lung cancer diagnosis and treatment.
6. Openness to exploring ethical considerations and challenges associated with implementing AI in medical settings.
7. Willingness to engage in discussions regarding the future of AI in healthcare and its implications for patient care and outcomes.

Speaker Info:

I, Arushi Garg, a seasoned researcher and dynamic speaker, bring a wealth of expertise to the forefront of AI-driven healthcare solutions. With a strong academic background and a passion for innovation, I have presented groundbreaking research findings at esteemed conferences worldwide.

As a speaker, I am known for my ability to articulate complex concepts with clarity and enthusiasm. My presentations blend theoretical insights with practical applications, providing audiences with valuable insights into the transformative potential of artificial intelligence in healthcare.

My research achievements include pioneering approaches such as sentiment analysis of movie reviews using CNN and LSTM models, fine-tuned frameworks with transfer learning for pulmonary disease diagnosis, and LSTM-based lung cancer classification. These contributions have been recognized by leading publishers such as Springer and IEEE, solidifying my reputation as a thought leader in the field.

Beyond academia, I am an active member of the tech community, serving as an AWS Cloud Captain and Founder of the AWS Cloud Club at IGDTUW. My commitment to fostering technical education and innovation underscores my dedication to advancing the field of AI in healthcare.

With a track record of engaging presentations and a deep understanding of cutting-edge technologies, I am poised to deliver a compelling talk that explores the transformative potential of AI for improved healthcare outcomes. Join me, Arushi Garg, as I share my insights and experiences, inspiring audiences to embrace the future of diagnostics with confidence and enthusiasm.

Speaker Links:

LinkedIn- https://www.linkedin.com/in/arushi-garg105 GitHub- https://github.com/072arushi Twitter- https://twitter.com/ArushiSpeaks105

In conclusion, my proposed talk promises to shed light on the groundbreaking advancements at the intersection of artificial intelligence and healthcare. Through an exploration of innovative research, practical applications, and real-world implications, attendees will gain a deeper understanding of the transformative power of AI in revolutionizing diagnostic methods. Together, let us embark on a journey towards a future where early detection, accurate diagnosis, and personalized treatment are not just possibilities, but realities. Join me as we pave the way for a healthier and brighter tomorrow. Thank you for considering my proposal.