Role of Predictive Models in Early Detection of Pancreatic Cancer

EasyChair Preprint no. 13645

Abstract

Pancreatic cancer is a highly lethal disease characterized by late-stage diagnosis and limited treatment options. Early detection plays a crucial role in improving patient outcomes and survival rates. Predictive models have emerged as valuable tools in the early detection of pancreatic cancer, leveraging data from various sources such as clinical records, genetic profiles, and imaging data. This abstract explores the role of predictive models in early detection, highlighting their potential benefits and limitations. The use of machine learning algorithms, statistical models, and risk prediction models is discussed, along with the types of data utilized and the features incorporated in these models. The training and validation processes involved in developing robust predictive models are also examined. The benefits of predictive models include enabling early intervention, improving patient outcomes, and reducing healthcare costs. However, challenges such as data availability, overfitting, and ethical considerations need to be addressed. This abstract presents case studies and success stories, showcasing the impact of predictive models on early detection rates. Furthermore, it explores future directions, including the integration of multi-modal data and advancements in machine learning techniques, which hold promise for personalized risk assessment and screening strategies. In conclusion, predictive models have the potential to revolutionize the early detection of pancreatic cancer, leading to improved patient outcomes and the optimization of healthcare systems. Continued research and collaboration are crucial for further advancements in this field.

Keyphrases: Challenges, data privacy, Data Quality, limitations, Overfitting, predictive models

@Booklet{EasyChair:13645,
  author = {Ayuns Luz},
  title = {Role of Predictive Models in Early Detection of Pancreatic Cancer},
  howpublished = {EasyChair Preprint no. 13645},

  year = {EasyChair, 2024}}