The growing interest in developing smart diagnostic systems to help medical experts
process extensive data for treating incurable diseases has been notable. In particular, the …

Multi-instance learning, a commonly used technique in artificial intelligence for analyzing
slides, can be applied to diagnose thyroid cancer based on cytological smears. Since …

Exploiting the capability of deep learning-based techniques, this research addresses an
important and relevant problem on how to cost effectively detect thyroid cancer. In recent …

Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …

Thyroid cancer, the most prevalent endocrine cancer, has gained significant global attention
due to its impact on public health. Extensive research efforts have been dedicated to …

Simple Summary The incidence of thyroid pathologies has been increasing worldwide.
Historically, the detection of thyroid neoplasms relies on medical imaging analysis …

Deep learning algorithms have achieved a tremendous triumph in task-specific feature
classification. Deep learning methods are very much effective when a large amount of …

Histopathological image contains rich phenotypic information, which is beneficial to
classifying tumor subtypes and predicting the development of diseases. The vast size of …

The diagnosis and management of thyroid cancer is fraught with challenges despite the
advent of innovative diagnostic, surgical, and chemotherapeutic modalities. Challenges like …

Background: Assessment of thyroid nodules histopathology using AI is crucial for an
accurate diagnosis. This systematic review analyzes recent works employing deep learning …