AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Human Growth Hormone

Showing 1 to 10 of 16 articles

Clear Filters

Weight loss-independent changes in human growth hormone during water-only fasting: a secondary evaluation of a randomized controlled trial.

Frontiers in endocrinology
INTRODUCTION: Water-only fasting for one day or more may provide health benefits independent of weight loss. Human growth hormone (HGH) may play a key role in multiple fasting-triggered mechanisms. Whether HGH changes during fasting are independent o...

Interpreting IGF-1 in children treated with recombinant growth hormone: challenges during early puberty.

Frontiers in endocrinology
OBJECTIVE: It can be challenging to determine the correct dosage of recombinant growth hormone (GH) in children with GH deficiency, leading to highly variable treatment responses. Insulin-like growth factor-1 (IGF-1) is a tool for monitoring GH treat...

Development and Validation of a Prediction Rule for Growth Hormone Deficiency Without Need for Pharmacological Stimulation Tests in Children With Risk Factors.

Frontiers in endocrinology
INTRODUCTION: Practice guidelines cannot recommend establishing a diagnosis of growth hormone deficiency (GHD) without performing growth hormone stimulation tests (GHST) in children with risk factors, due to the lack of sufficient evidence.

Machine learning-based prediction of response to growth hormone treatment in Turner syndrome: the LG Growth Study.

Journal of pediatric endocrinology & metabolism : JPEM
Background Growth hormone (GH) treatment has become a common practice in Turner syndrome (TS). However, there are only a few studies on the response to GH treatment in TS. The aim of this study is to predict the responsiveness to GH treatment and to ...

Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature.

Journal of clinical research in pediatric endocrinology
Assessment and management of children with growth failure has improved greatly over recent years. However, there remains a strong potential for further improvements by using novel digital techniques. A panel of experts discussed developments in digit...

Using Deep Learning for Individual-Level Predictions of Adherence with Growth Hormone Therapy.

Studies in health technology and informatics
The problem of consistent therapy adherence is a current challenge for health informatics, and its solution can increase the success rate of treatments. Here we show a methodology to predict, at individual-level, future therapy adherence for patients...

Digital technologies to improve the precision of paediatric growth disorder diagnosis and management.

Growth hormone & IGF research : official journal of the Growth Hormone Research Society and the International IGF Research Society
Paediatric disorders of impaired linear growth are challenging to manage, in part because of delays in the identification of pathological short stature and subsequent referral and diagnosis, the requirement for long-term therapy, and frequent poor ad...

Machine Learning-based Prediction Model for Treatment of Acromegaly With First-generation Somatostatin Receptor Ligands.

The Journal of clinical endocrinology and metabolism
CONTEXT: Artificial intelligence (AI), in particular machine learning (ML), may be used to deeply analyze biomarkers of response to first-generation somatostatin receptor ligands (fg-SRLs) in the treatment of acromegaly.

Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device.

BMC medical informatics and decision making
BACKGROUND: Our aim was to develop a machine learning model, using real-world data captured from a connected auto-injector device and from early indicators from the first 3 months of treatment, to predict sub-optimal adherence to recombinant human gr...

Pituitary MRI Radiomics Improves Diagnostic Performance of Growth Hormone Deficiency in Children Short Stature: A Multicenter Radiomics Study.

Academic radiology
RATIONALE AND OBJECTIVES: To develop an efficient machine-learning model using pituitary MRI radiomics and clinical data to differentiate growth hormone deficiency (GHD) from idiopathic short stature (ISS), making the diagnostic process more acceptab...