[HTML][HTML] Early prediction of hypothyroidism and multiclass classification using predictive machine learning and deep learning
Thyroid disease is considered one of the most common health disorders, which may lead to
various health problems. Recent studies reveal that approximately 42 million people in India …
various health problems. Recent studies reveal that approximately 42 million people in India …
Thyroid disease prediction using selective features and machine learning techniques
Simple Summary The study presents a thyroid disease prediction approach which utilizes
random forest-based features to obtain high accuracy. The approach can obtain a 0.99 …
random forest-based features to obtain high accuracy. The approach can obtain a 0.99 …
Computer-aided diagnosis systems: a comparative study of classical machine learning versus deep learning-based approaches
The diagnostic phase of the treatment process is essential for patient guidance and follow-
up. The accuracy and effectiveness of this phase can determine the life or death of a patient …
up. The accuracy and effectiveness of this phase can determine the life or death of a patient …
Early thyroid risk prediction by data mining and ensemble classifiers
MH Alshayeji - Machine Learning and Knowledge Extraction, 2023 - mdpi.com
Thyroid disease is among the most prevalent endocrinopathies worldwide. As the thyroid
gland controls human metabolism, thyroid illness is a matter of concern for human health. To …
gland controls human metabolism, thyroid illness is a matter of concern for human health. To …
Machine learning framework with feature selection approaches for thyroid disease classification and associated risk factors identification
A Sultana, R Islam - Journal of Electrical Systems and Information …, 2023 - Springer
Thyroid disease (TD) develops when the thyroid does not generate an adequate quantity of
thyroid hormones as well as when a lump or nodule emerges due to aberrant growth of the …
thyroid hormones as well as when a lump or nodule emerges due to aberrant growth of the …
Modeling and regulation of thyroid feedback network based on DNA strand displacement
J Sun, C Sun, Z Wang, Y Wang - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The Internet of Things has shown great advantages in intelligent healthcare applications. In
this article, based on the idea of Internet of Things application in intelligent healthcare, the …
this article, based on the idea of Internet of Things application in intelligent healthcare, the …
An Improved Framework for Detecting Thyroid Disease Using Filter-Based Feature Selection and Stacking Ensemble
In recent years, machine learning (ML) has become a pivotal tool for predicting and
diagnosing thyroid disease. While many studies have explored the use of individual ML …
diagnosing thyroid disease. While many studies have explored the use of individual ML …
Detecting thyroid disease using optimized machine learning model based on differential evolution
Thyroid disease has been on the rise during the past few years. Owing to its importance in
metabolism, early detection of thyroid disease is a task of critical importance. Despite …
metabolism, early detection of thyroid disease is a task of critical importance. Despite …
A Detailed Investigation and Analysis of Using Machine Learning Techniques for Thyroid Diagnosis
A Method of Classification Based on Norms Data mining greatly benefits several subfields
within the healthcare industry. Detecting and treating diseases at an early stage is a …
within the healthcare industry. Detecting and treating diseases at an early stage is a …
An intelligent thyroid diagnosis system utilising multiple ensemble and explainable algorithms with medical supported attributes
The widespread impact of thyroid disease and its diagnosis is a challenging task for
healthcare experts. The conventional technique for predicting such a vital disease is …
healthcare experts. The conventional technique for predicting such a vital disease is …