Theoretical and experimental approaches to study of biological objects by mathematical methods using the example of hormone production in the thyroid gland
The study of any biological object is a complex process that involves a number of successive
stages, one of which tools can be a specially created expert system. It is advisable to present …
stages, one of which tools can be a specially created expert system. It is advisable to present …
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 …
Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models
Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to
either hyperthyroidism or hypothyroidism, which can significantly impact metabolism and …
either hyperthyroidism or hypothyroidism, which can significantly impact metabolism and …
Analysis and interpretability of machine learning models to classify thyroid disease
Thyroid disease classification plays a crucial role in early diagnosis and effective treatment
of thyroid disorders. Machine learning (ML) techniques have demonstrated remarkable …
of thyroid disorders. Machine learning (ML) techniques have demonstrated remarkable …
Fuzzy machine learning logic utilization on hormonal imbalance dataset
In this research work, a novel fuzzy data transformation technique has been proposed and
applied to the hormonal imbalance dataset. Hormonal imbalance is ubiquitously found …
applied to the hormonal imbalance dataset. Hormonal imbalance is ubiquitously found …
[HTML][HTML] Enhancing thyroid disease prediction and comorbidity management through advanced machine learning frameworks
Thyroid disease is one of the most prevalent endocrine disorders worldwide, necessitating
precise and efficient diagnostic models for improved clinical outcomes. This study proposes …
precise and efficient diagnostic models for improved clinical outcomes. This study proposes …
[PDF][PDF] Modeling and Predictive Analytics of Breast Cancer Using Ensemble Learning Techniques: An Explainable Artificial Intelligence Approach.
Breast cancer stands as one of the world's most perilous and formidable diseases, having
recently surpassed lung cancer as the most prevalent cancer type. This disease arises when …
recently surpassed lung cancer as the most prevalent cancer type. This disease arises when …
Machine Learning Models for Predicting Hypothyroidism: Utilizing Synthetic Data for Improved Accuracy
If left untreated, hypothyroidism, a common endocrine illness, can result in a number of
health issues due to the underactive thyroid gland. Accurately predicting hypothyroidism is …
health issues due to the underactive thyroid gland. Accurately predicting hypothyroidism is …
Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms
In the contemporary world, thyroid disease poses a prevalent health issue, particularly
affecting women's well-being. Recognizing the significance of maternal thyroid (MT) …
affecting women's well-being. Recognizing the significance of maternal thyroid (MT) …
An Integrated Analysis of Deep Learning and Machine Learning for Thyroid Disease Detection
There has been a rapid implementation of artificial intelligence technologies in health care
systems. Neural networks, machine learning, deep learning, and other types of learning are …
systems. Neural networks, machine learning, deep learning, and other types of learning are …