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Machine learning (ML) applications have received extensive attention in endocrinology research during the last decade. This review summarizes the basic concepts of ML and certain research topics in endocrinology and metabolism where ML principles have been actively deployed. Relevant studies are discussed to provide an overview of the methodology, main findings, and limitations of ML, with the goal of stimulating insights into future research directions. Clear, testable study hypotheses stem from unmet clinical needs, and the management of data quality (beyond a focus on quantity alone), open collaboration between clinical experts and ML engineers, the development of interpretable high-performance ML models beyond the black-box nature of some algorithms, and a creative environment are the core prerequisites for the foreseeable changes expected to be brought about by ML and artificial intelligence in the field of endocrinology and metabolism, with actual improvements in clinical practice beyond hype. Of note, endocrinologists will continue to play a central role in these developments as domain experts who can properly generate, refine, analyze, and interpret data with a combination of clinical expertise and scientific rigor.
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Branched-chain amino acids (BCAAs) are essential amino acids that are not synthesized in our body; thus, they need to be obtained from food. They have shown to provide many physiological and metabolic benefits such as stimulation of pancreatic insulin secretion, milk production, adipogenesis, and enhanced immune function, among others, mainly mediated by mammalian target of rapamycin (mTOR) signaling pathway. After identified as a reliable marker of obesity and type 2 diabetes in recent years, an increasing number of studies have surfaced implicating BCAAs in the pathophysiology of other diseases such as cancers, cardiovascular diseases, and even neurodegenerative disorders like Alzheimer's disease. Here we discuss the most recent progress and review studies highlighting both correlational and potentially causative role of BCAAs in the development of these disorders. Although we are just beginning to understand the intricate relationships between BCAAs and some of the most prevalent chronic diseases, current findings raise a possibility that they are linked by a similar putative mechanism.
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