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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 challenge of identifying thyroid cancer (TC) has seen progress…

机器学习 · 计算机科学 2025-12-19 Yassine Habchi , Hamza Kheddar , Yassine Himeur , Mohamed Chahine Ghanem

Differentiated thyroid cancer DTC recurrence is a major public health concern, requiring classification and predictive models that are not only accurate but also interpretable and uncertainty aware. This study introduces a comprehensive…

机器学习 · 计算机科学 2025-07-28 HMNS Kumari , HMLS Kumari , UMMPK Nawarathne

There has been a growing interest in creating intelligent diagnostic systems to assist medical professionals in analyzing and processing big data for the treatment of incurable diseases. One of the key challenges in this field is detecting…

图像与视频处理 · 电气工程与系统科学 2023-08-29 Yassine Habchi , Yassine Himeur , Hamza Kheddar , Abdelkrim Boukabou , Shadi Atalla , Ammar Chouchane , Abdelmalik Ouamane , Wathiq Mansoor

Thyroid cancer is currently the fifth most common malignancy diagnosed in women. Since differentiation of cancer sub-types is important for treatment and current, manual methods are time consuming and subjective, automatic computer-aided…

Thyroid cancer is a common endocrine carcinoma that occurs in the thyroid gland. Much effort has been invested in improving its diagnosis, and thyroidectomy remains the primary treatment method. A successful operation without unnecessary…

机器学习 · 计算机科学 2022-03-31 Nan Miles Xi , Lin Wang , Chuanjia Yang

In oncology, recurrence after treatment is one of the major challenges, related to patients' survival and quality of life. Conventionally, prediction of cancer relapse has always relied on clinical observation with statistical model…

机器学习 · 计算机科学 2025-02-25 Muhammad Umer Qayyum , Muhammad Fahad , Nasrullah Abbasi

Thyroid disease instances have been continuously increasing since the 1990s, and thyroid cancer has become the most rapidly rising disease among all the malignancies in recent years. Most existing studies focused on applying deep…

图像与视频处理 · 电气工程与系统科学 2022-03-09 Xinyu Zhang , Vincent CS. Lee , Jia Rong , James C. Lee , Jiangning Song , Feng Liu

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 leveraging artificial intelligence (AI) methods for the early…

机器学习 · 计算机科学 2024-01-09 Xinyu Zhang , Vincent CS Lee , Feng Liu

Thyroid cancer is common worldwide, with a rapid increase in prevalence across North America in recent years. While most patients present with palpable nodules through physical examination, a large number of small and medium-sized nodules…

The past years have seen a considerable increase in cancer cases. However, a cancer diagnosis is often complex and depends on the types of images provided for analysis. It requires highly skilled practitioners but is often time-consuming…

图像与视频处理 · 电气工程与系统科学 2022-10-24 Solene Bechelli

The ability to explain the prediction of deep learning models to end-users is an important feature to leverage the power of artificial intelligence (AI) for the medical decision-making process, which is usually considered non-transparent…

计算机视觉与模式识别 · 计算机科学 2023-03-09 Truong Thanh Hung Nguyen , Van Binh Truong , Vo Thanh Khang Nguyen , Quoc Hung Cao , Quoc Khanh Nguyen

Thyroid cancer is an increasing global health concern that requires advanced diagnostic methods. The application of AI and radiomics to thyroid cancer diagnosis is examined in this review. A review of multiple databases was conducted in…

Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning offers a promising solution, while the development of such…

Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise…

This research presents an innovative approach to cancer diagnosis and prediction using explainable Artificial Intelligence (XAI) and deep learning techniques. With cancer causing nearly 10 million deaths globally in 2020, early and accurate…

人工智能 · 计算机科学 2024-12-24 Badaru I. Olumuyiwa , The Anh Han , Zia U. Shamszaman

We present a mechanistic biomathematical model of molecular radiotherapy of thyroid disease. The general model consists of a set of differential equations describing the dynamics of different populations of thyroid cells with varying…

医学物理 · 物理学 2021-10-15 Araceli Gago-Arias , Sara Neira , Filippo Terragni , Juan Pardo-Montero

Thyroid cancer is the most common endocrine malignancy, and accurately distinguishing between benign and malignant thyroid tumors is crucial for developing effective treatment plans in clinical practice. Pathologically, thyroid tumors pose…

图像与视频处理 · 电气工程与系统科学 2024-01-04 Jia Dong , Yao Yao , Yang Dong , Hui Ma

Over the past decades, the incidence of thyroid cancer has been increasing globally. Accurate and early diagnosis allows timely treatment and helps to avoid over-diagnosis. Clinically, a nodule is commonly evaluated from both transverse and…

计算机视觉与模式识别 · 计算机科学 2022-07-04 Han Huang , Yijie Dong , Xiaohong Jia , Jianqiao Zhou , Dong Ni , Jun Cheng , Ruobing Huang

Purpose: Thyroid cancer has been a common cancer. Papillary thyroid cancer and follicular thyroid cancer are the two most common types of thyroid cancer. Follicular thyroid cancer lacks distinctive ultrasound signs and is more difficult to…

机器学习 · 计算机科学 2025-09-17 Songlin Zhou , Tao Zhou , Xin Li , Stephen Shing-Toung Yau

Accurate prediction of recurrence in clear cell renal cell carcinoma (ccRCC) remains a major clinical challenge due to the disease complex molecular, pathological, and clinical heterogeneity. Traditional prognostic models, which rely on…

图像与视频处理 · 电气工程与系统科学 2025-07-11 Hasaan Maqsood , Saif Ur Rehman Khan
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