Computer-aided diagnosis systems: a comparative study of classical machine learning versus deep learning-based approaches

R Guetari, H Ayari, H Sakly - Knowledge and Information Systems, 2023 - Springer
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 …

[HTML][HTML] Early prediction of hypothyroidism and multiclass classification using predictive machine learning and deep learning

K Guleria, S Sharma, S Kumar, S Tiwari - Measurement: Sensors, 2022 - Elsevier
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 …

[HTML][HTML] Thyroid disease prediction using selective features and machine learning techniques

R Chaganti, F Rustam, I De La Torre Díez, JLV Mazón… - Cancers, 2022 - mdpi.com
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 …

Detecting thyroid disease using optimized machine learning model based on differential evolution

P Gupta, F Rustam, K Kanwal, W Aljedaani… - International Journal of …, 2024 - Springer
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 …

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 …

[HTML][HTML] 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 …

An improved framework for detecting thyroid disease using filter-based feature selection and stacking ensemble

G Obaido, O Achilonu, B Ogbuokiri, CS Amadi… - IEEE …, 2024 - ieeexplore.ieee.org
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 …

A novel meta learning based stacked approach for diagnosis of thyroid syndrome

MA Abbas, K Munir, A Raza, M Amjad, NA Samee… - PLoS …, 2024 - journals.plos.org
Thyroid syndrome, a complex endocrine disorder, involves the dysregulation of the thyroid
gland, impacting vital physiological functions. Common causes include autoimmune …

An Intelligent Thyroid Diagnosis System Utilizing Multiple Ensemble and Explainable Algorithms With Medical Supported Attributes

A Sutradhar, M Al Rafi, P Ghosh… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
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 …

A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing …

O Tutsoy, HE Sumbul - Briefings in Bioinformatics, 2024 - academic.oup.com
Thyroid cancer incidences endure to increase even though a large number of inspection
tools have been developed recently. Since there is no standard and certain procedure to …