Handling imbalanced medical datasets: review of a decade of research
Abstract Machine learning and medical diagnostic studies often struggle with the issue of
class imbalance in medical datasets, complicating accurate disease prediction and …
class imbalance in medical datasets, complicating accurate disease prediction and …
Comparative analysis of machine learning techniques for indian liver disease patients
MA Kuzhippallil, C Joseph… - 2020 6th International …, 2020 - ieeexplore.ieee.org
Machine Learning has a strong potential in automated diagnosis of various diseases. With
the recent upscale in various liver diseases, it is necessary to identify the liver disease at a …
the recent upscale in various liver diseases, it is necessary to identify the liver disease at a …
Sentiment Prediction of Textual Data Using Hybrid ConvBidirectional‐LSTM Model
With the emergence of social media platforms, most people have changed their way of
interacting. Perhaps, sharing day‐to‐day lifestyle updates is a trend substantially influenced …
interacting. Perhaps, sharing day‐to‐day lifestyle updates is a trend substantially influenced …
[PDF][PDF] An Approach Using Fuzzy Sets and Boosting Techniques to Predict Liver Disease.
P Kumar, RS Thakur - Computers, Materials & Continua, 2021 - cdn.techscience.cn
The aim of this research is to develop a mechanism to help medical practitioners predict and
diagnose liver disease. Several systems have been proposed to help medical experts by …
diagnose liver disease. Several systems have been proposed to help medical experts by …
A novel machine learning approach using boosting algorithm for liver disease classification
Machine learning has been highly recommended in medical sector for diagnosis of several
diseases and for effective decision making due to its performance. With recent years, there is …
diseases and for effective decision making due to its performance. With recent years, there is …
Hematological image analysis for segmentation and characterization of erythrocytes using FC-TriSDR
P Kumar, KS Babulal - Multimedia tools and applications, 2023 - Springer
In medical science, the scrutiny of blood smears for the abnormality in erythrocyte, leads to
decisive determination of several ailments like Thalasemia, Liver disease, Sickle cell …
decisive determination of several ailments like Thalasemia, Liver disease, Sickle cell …
[PDF][PDF] Hierarchical Bi-LSTM based emotion analysis of textual data
Nowadays, Twitter is one of the most popular microblogging sites that is generating a
massive amount of textual data. Such textual data is intended to incorporate human feelings …
massive amount of textual data. Such textual data is intended to incorporate human feelings …
The diagnosis of chronic liver disease using machine learning techniques
G Shaheamlung, H Kaur - Information Technology in Industry, 2021 - it-in-industry.org
In the 21st-century, the issue of liver disease has been increasing all over the world. As per
the latest survey report, liver disease death toll has been rise approximately 2 million per …
the latest survey report, liver disease death toll has been rise approximately 2 million per …
Detection of Liver Disease Using Machine Learning Approach
For more effective therapy, it's critical to get an early diagnosis of liver illness. Due to the
disease's modest symptoms, it is a very difficult challenge for medical experts to forecast the …
disease's modest symptoms, it is a very difficult challenge for medical experts to forecast the …
Categorical data clustering using harmony search algorithm for healthcare datasets
Healthcare analytics provide many benefits in healthcare dashboard systems. Healthcare
datasets majorly contains categorical attributes. This paper proposed an optimized …
datasets majorly contains categorical attributes. This paper proposed an optimized …