AIMC Topic: Thyroxine

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From objective grouping to fuzzy reference intervals: A standardized machine learning approach for thyroid function tests.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Accurate interpretation of thyroid function tests (TFTs) requires reliable reference intervals (RIs). Indirect methods based on retrospective laboratory data are increasingly used, but current strategies face major limitations, including ...

Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data.

BMJ open
OBJECTIVES: To develop and validate a machine learning (ML) model to differentiate malignant from benign thyroid nodules (TNs) based on the routine data and provide diagnostic assistance for medical professionals.

Developing a machine learning-based predictive model for levothyroxine dosage estimation in hypothyroid patients: a retrospective study.

Frontiers in endocrinology
Hypothyroidism, a common endocrine disorder, has a high incidence in women and increases with age. Levothyroxine (LT4) is the standard therapy; however, achieving clinical and biochemical euthyroidism is challenging. Therefore, developing an accurate...

The predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis in patients with differentiated thyroid cancer.

Annals of medicine
OBJECTIVE: To comprehensively investigate the predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis in patients diagnosed with differentiated thyroid cancer (DTC) undergoing total thyroidectomy and neck lymph n...

Binding and sensing diverse small molecules using shape-complementary pseudocycles.

Science (New York, N.Y.)
We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying sha...

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial.

Clinical pharmacology and therapeutics
Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to high-interindividual differences in effective dosage and the narrow therapeutic window. Model-informed precision dosing (MIPD) using machine learning...

Pediatric Psoriasis Associated with Van Wyk Grumbach Syndrome: A case report.

La Tunisie medicale
INTRODUCTION: Psoriasis is a common chronic inflammatory condition, often beginning in childhood in approximately one-third of cases. It can be associated with various other autoimmune diseases such as rheumatoid arthritis, celiac disease, and thyroi...

Machine learning to improve false-positive results in the Dutch newborn screening for congenital hypothyroidism.

Clinical biochemistry
OBJECTIVE: The Dutch Congenital hypothyroidism (CH) Newborn Screening (NBS) algorithm for thyroidal and central congenital hypothyroidism (CH-T and CH-C, respectively) is primarily based on determination of thyroxine (T4) concentrations in dried bloo...

The Prevalence of Euthyroid Hypertriiodothyroninemia in Newly Diagnosed Multiple Myeloma and its Clinical Characteristics.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: To evaluate the prevalence of euthyroid hypertriiodothyroninemia and/or hyperthyroxinemia and its clinical characteristics in multiple myeloma (MM) patients.

Artificial intelligence may offer insight into factors determining individual TSH level.

PloS one
The factors that determine Serum Thyrotropin (TSH) levels have been examined through different methods, using different covariates. However, the use of machine learning methods has so far not been studied in population databases like NHANES (National...