Artificial Intelligence & Machine Learning Models to Predict Thyroid Cancer during Pregnancy: A Review

Abstract

Thyroid cancer is the second most prevalent cancer diagnosed during pregnancy, after breast cancer. Controlling cancer and averting problems caused by maternal hypothyroidism are the main objectives of therapy. There was no clear association found when the role of female sex hormones as an etiologic factor was investigated. Pregnancy may trigger an existing thyroid nodule to enlarge owing to the structural similarities between TSH and BHCG as well as the naturally generated oestrogen receptors on thyroid gland cells. Pregnancy's impact on the development and prognosis of differentiated thyroid tumors (follicular and papillary) has also been studied. Patients with thyroid cancer who were diagnosed while pregnant or who became pregnant after receiving curative treatment do not have a worse prognosis. Pregnancy termination is not at all advised; surgery can wait until after delivery, except for malignant tumors that are growing quickly. While radioactive iodine ablation is categorically contraindicated during pregnancy, the novel systemic therapies are not thoroughly researched. But almost most of these new substances are FDA categories C or D, which means they should be avoided. Pregnancy's effect on other types of thyroid cancer (medullary and anaplastic thyroid tumors) has not been extensively investigated because of the rarity of pregnancy is. It is crucial to control thyroid cancer endocrinologically while pregnant. Fetal hypothyroidism may result from the hypothyroidism brought on by a complete thyroidectomy. A multidisciplinary team is therefore required for the care of thyroid cancer linked to pregnancy. Here, we provide Artificial Intelligence & Machine Learning based predictions for early intervention by the medical fraternity in Thyroid Cancer during Pregnancy.

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