Kidney Tumour Detection Using Deep Neural Network
Journal Title: International Journal of Innovative Research in Computer Science and Technology - Year 2022, Vol 10, Issue 5
Abstract
Classifying the malignancy of a renal tumour is one of the most important urological duties because it plays a key role in determining whether or not to undergo kidney removal surgery (nephrectomy). Currently, the radiological diagnostic made us89++ing computed tomography (CT) scans determines the likelihood of a tumour being malignant. However, it's believed that up to 16 percent of nephrectomies may have been avoided since a postoperative histological study revealed that a tumour that had been first identified as malignant was actually benign. Numerous false-positive diagnoses lead to unnecessary nephrectomies, which increase the chance of post-procedural problems. In this article, we offer a computer-aided diagnostic method that analyses a CT scan to determine the tumour’s malignancy. The prediction, which is used to identify false-positive diagnoses, is carried out following radiological diagnosis. Our solution can complete this challenge with an F1 score of 0.84. Additionally, we suggest a cutting-edge method for knowledge transmission in the medical field using colorization-based pre-processing, which can raise the F1-score by as much as to 1.8.
Authors and Affiliations
Tawseeful Haziq, Ashish Obroi, and Yogesh
Keywords
Related Articles
- EP ID EP746028
- DOI 10.55524/ijircst.2022.10.5.2
- Views 2
- Downloads 0
Knowledge Representation for Legal Document Summarization
This paper presents a novel approach for legal document summarization. Proposed approach is based on Ripple-Down Rules (RDR). It is an incremental knowledge acquisition method. RDR allows us to quickly build an extendabl...
Integrating Monistic Theory, Neuro-Linguistic Programming, and AI for Developing Emotionally Healthy School Children- A Global and Indian Perspective
Emotional health plays a crucial role in the holistic development of school children, impacting their academic performance, social interactions, and overall well-being. This research article explores the potential of int...
Assessing the Impact of International Personnel on Local Community Dynamics
This research investigates the multifaceted impact of international personnel on local communities in Greater Noida, India, exploring socio-economic, cultural, and integrative dynamics through empirical data collected fr...
Refining Credit Risk Analysis- Integrating Bayesian MCMC with Hamiltonian Monte Carlo
The accurate prediction of loan defaults is paramount for financial institutions to enhance decision-making processes, optimize loan approval rates, and mitigate associated risks. This study develops a predictive model u...
A Review Article On Enhancing Email Spam Filter’s Accuracy Using Machine Learning
In today’s era, almost everyone is using emails on their daily basis. In our proposed research, we suggest a machine learning-based strategy for enhancing email spam filters' accuracy. Traditional rule-based filters have...