Detecting Non-Alcoholic Fatty Liver Disease (NAFLD) using Clinical Reports

9 pages•Published: August 6, 2024

Lakshmi Warrier, Devika M, Perumalla Raghavendra and Remya S

Abstract

Non-Alcoholic Fatty Liver Disease (NAFLD) is a prevalent liver condition that necessi- tates accurate and non-invasive diagnostic approaches for effective treatment. This research addresses the challenges associated with present invasive procedures, such as liver biopsies, and proposes a novel diagnostic tool. Inspired by the limitations of existing methods, our project focuses on revolutionizing routine check-ups for middle-aged individuals at risk of NAFLD. Instead of traditional invasive biopsies, our diagnostic tool recommends a blood test, ensuring accurate identification and timely intervention. The conventional diagnostic methods for NAFLD involve imaging and invasive procedures, leading to accessibility and accuracy issues. In response, our user-friendly web application utilizes standard blood test findings to provide a quick and painless NAFLD diagnosis. This approach aims to create an affordable, easily accessible tool that minimizes patient discomfort. Leveraging a dataset of 3,237 individuals from NHANES III, our model achieves an outstanding accuracy rate of 89%. The dataset includes both NAFLD-positive and NAFLD-negative cases, ensur- ing a robust and representative model. In summary, this work makes significant strides in developing a blood-based, non-invasive method that enhances accessibility to NAFLD diagnostics through a user-friendly web application. The proposed tool offers a convenient option for patients and equips healthcare providers with an effective NAFLD diagnostic tool, fostering better patient care outcomes through early detection and intervention.

Keyphrases: biomarkers, deep learning, hepatic steatosis, nafld, non invasive technique, ultrasound imaging

In: Rajakumar G (editor). Proceedings of 6th International Conference on Smart Systems and Inventive Technology, vol 19, pages 488-496.

Links:	https://easychair.org/publications/paper/jMF8
	https://doi.org/10.29007/6x7w

BibTeX entry

@inproceedings{ICSSIT2024:Detecting_Non_Alcoholic_Fatty,
  author    = {Lakshmi Warrier and Devika M and Perumalla Raghavendra and Remya S},
  title     = {Detecting Non-Alcoholic Fatty Liver Disease (NAFLD) using Clinical Reports},
  booktitle = {Proceedings of 6th International Conference on Smart Systems and Inventive Technology},
  editor    = {Rajakumar G},
  series    = {Kalpa Publications in Computing},
  volume    = {19},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/jMF8},
  doi       = {10.29007/6x7w},
  pages     = {488-496},
  year      = {2024}}

Download PDF Open PDF in browser