M. L. Maruthi Prasad^*, R. Santhosh

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 1-13, 2024, DOI:10.32604/iasc.2023.036628 - 29 March 2024

Abstract This research concentrates to model an efficient thyroid prediction approach, which is considered a baseline for significant problems faced by the women community. The major research problem is the lack of automated model to attain earlier prediction. Some existing model fails to give better prediction accuracy. Here, a novel clinical decision support system is framed to make the proper decision during a time of complexity. Multiple stages are followed in the proposed framework, which plays a substantial role in thyroid prediction. These steps include i) data acquisition, ii) outlier prediction, and iii) multi-stage weight-based ensemble More >

BINGJIE WANG¹, YEWEN ZHOU^1,2,3, TONGJUAN NIU¹, MENGQING YIN¹, SHENG CUI^1,2,3,*

BIOCELL, Vol.48, No.2, pp. 327-338, 2024, DOI:10.32604/biocell.2023.044630 - 23 February 2024

Abstract Introduction: The regulation of thyroid-stimulating hormone (TSH) synthesis involves neurotransmitters, with melatonin being a subject of ongoing debate. TSH transcription, synthesis, and secretion from the pituitary pars distalis (PD) is primarily regulated in a photoperiodic manner by thyrotropin-releasing hormone (TRH). In contrast, in the pituitary pars tuberalis (PT), mRNA transcription and alpha/beta chain synthesis, but not secretion, of a TSH-like product is regulated by melatonin. Conversely, non-photoperiodic melatonin might also affect the secretion of a TSH-like product from the PT. Nevertheless, the impact of exogenous melatonin on the underlying PD-TSH synthesis remains unclear. Casein kinase… More >

Lu Chen^1,#, Huaqiang Chen^2,#, Zhikai Pan⁷, Sheng Xu², Guangsheng Lai², Shuwen Chen^2,5,6, Shuihua Wang^3,8, Xiaodong Gu^2,6,*, Yudong Zhang^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 361-382, 2024, DOI:10.32604/cmes.2023.031229 - 30 December 2023

Abstract Aim: This study aims to establish an artificial intelligence model, ThyroidNet, to diagnose thyroid nodules using deep learning techniques accurately. Methods: A novel method, ThyroidNet, is introduced and evaluated based on deep learning for the localization and classification of thyroid nodules. First, we propose the multitask TransUnet, which combines the TransUnet encoder and decoder with multitask learning. Second, we propose the DualLoss function, tailored to the thyroid nodule localization and classification tasks. It balances the learning of the localization and classification tasks to help improve the model’s generalization ability. Third, we introduce strategies for augmenting… More >

FABIANA ROCHA ARAÚJO¹, BRUNO MACHADO BERTASSOLI², ISABELLA CRISTINA SOUZA FÉLIX¹, DOUGLAS MARINHO ABREU¹, NATáLIA MELO OCARINO¹, AMANDA MARIA SENA REIS³, JUNEO FREITAS SILVA⁴, ROGéRIA SERAKIDES^1,*

BIOCELL, Vol.47, No.2, pp. 423-430, 2023, DOI:10.32604/biocell.2023.023689 - 18 November 2022

Abstract To evaluate the characteristics and synthesis activity of osteoblasts extracted from the calvaria of offspring of rats exposed to maternal hyperthyroidism. Twelve adult Wistar rats were divided into two groups, one control and one treated with daily administration of L-thyroxine by an orogastric tube (50 µg/animal/day) during pregnancy. Three days after delivery and confirmation of the mothers’ hyperthyroidism, the offspring were euthanized for the extraction of osteoblasts from the calvaria. At 7, 14, and 21 days, proliferation activity was assessed using MTT assay, while alkaline phosphatase (ALP) activity was assessed by the BCIP/NBT method. At… More >

S. J. K. Jagadeesh Kumar¹, P. Parthasarathi², Mehedi Masud³, Jehad F. Al-Amri⁴, Mohamed Abouhawwash^5,6,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2909-2924, 2023, DOI:10.32604/iasc.2023.030335 - 17 August 2022

Abstract The main task of thyroid hormones is controlling the metabolism rate of humans, the development of neurons, and the significant growth of reproductive activities. In medical science, thyroid disorder will lead to creating thyroiditis and thyroid cancer. The two main thyroid disorders are hyperthyroidism and hypothyroidism. Many research works focus on the prediction of thyroid disorder. To improve the accuracy in the classification of thyroid disorder this paper proposes optimization-based feature selection by using differential evolution with the Butterfly optimization algorithm (DE-BOA). For the classifier fuzzy C-means algorithm (FCM) is used. The proposed DEBOA-FCM is More >

Soma Prathibha^1,*, Deepak Dahiya², C. R. Rene Robin³, Cherukuru Venkata Nishkala⁴, S. Swedha⁵

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 199-214, 2023, DOI:10.32604/iasc.2023.025819 - 06 June 2022

Abstract Thyroid disease is a medical condition caused due to the excess release of thyroid hormone. It is released by the thyroid gland which is in front of the neck just below the larynx. Medical pictures such as X-rays and CT scans can, however, be used to diagnose it. In this proposed model, Deep Learning technology is used to detect thyroid diseases. A Convolution Neural Network (CNN) based modified ResNet architecture is employed to detect five different types of thyroid diseases namely 1. Hypothyroid 2. Hyperthyroid 3. Thyroid cancer 4. Thyroiditis 5. Thyroid nodules. In the… More >

Federico Cappellacci^*, Gian Luigi Canu, Stefano Piras, Giacomo Anedda, Pietro Giorgio Calò, Fabio Medas

Oncologie, Vol.24, No.1, pp. 35-50, 2022, DOI:10.32604/oncologie.2022.020864 - 31 March 2022

Abstract Thyroid cancer is the fifth most common cancer in the USA, with differentiated subtype accounting for more than 95% of neoplasm. Surgery remains the mainstay of treatment, either with lobectomy or total thyroidectomy. In the last decades, many technological innovations have been introduced in this field. The aim of this review is to illustrate the most recent advances regarding the classical surgical approach, particularly regarding hemostatic devices, parathyroid identification with fluorescence systems, intraoperative identification of lymph node metastases, and intraoperative neuromonitoring. More >

Yanling An¹, Shaohai Hu^1,*, Shuaiqi Liu^2,3, Jie Zhao^2,3,*, Yu-Dong Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 203-222, 2021, DOI:10.32604/cmes.2021.015159 - 28 June 2021

Abstract This paper proposes a computer-aided diagnosis system which can automatically detect thyroid nodules (TNs) and discriminate them as benign or malignant. The system firstly uses variational level set active contour with gradients and phase information to complete automatic extraction of the boundaries of thyroid nodules images. Then according to thyroid ultrasound images and clinical diagnostic criteria, a new feature extraction method based on the fusion of shape, gray and texture is explored. Due to the imbalance of thyroid sample classes, this paper introduces a weight factor to improve support vector machine, offering different classes of More >

Yu Xiao¹, Peng Zhou², Yizi Zheng¹, Chang Zheng¹, Guowen Liu¹, Weixiang Liu^3,*

Oncologie, Vol.23, No.2, pp. 219-228, 2021, DOI:10.32604/Oncologie.2021.016480 - 22 June 2021

Abstract The elevation for lateral lymph node metastasis (LLNM) plays an important role in therapeutic decision-making for thyroid carcinoma. A reliable forecasting model for LLNM in patients with papillary thyroid micro-carcinoma (PTMC) is needed, using clinicopathological characteristics. A total of 576 PTMC patients with suspicious lateral cervical lymph node (II, III, IV or V region) metastasis and known clinicopathological variables were randomly collected at Shenzhen Second People’s Hospital. Cervical lymph node status of every patient was assessed by ultrasonography (US). The patients in this cohort study underwent thyroidectomy and lateral neck lymph node dissection. Univariate analysis… More >

Hyeong Won Yu¹, Muhammad Afzal², Maqbool Hussain², Hyungju Kwon³, Young Joo Park⁴, June Young Choi^1,*, Kyu Eun Lee⁵

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1241-1251, 2021, DOI:10.32604/cmc.2021.014910 - 12 January 2021

Abstract Advances in technology are enabling gene mutations in papillary thyroid carcinoma (PTC) to be analyzed and clinical outcomes, such as recurrence, to be predicted. To date, the most common genetic mutation in PTC is in BRAF kinase (BRAF). However, whether mutations in other genes coincide with those in BRAF remains to be clarified. The aim of this study was to find mutations in other genes that co-exist with mutated BRAF, and to analyze their frequency and clinical relevance in PTC. Clinical and genetic data were collected from 213 PTC patients with a total of 36,572… More >