ArticleIndian journal of endocrinology and metabolism
Artificial Intelligence in the Management of Obesity.
Article in Indian journal of endocrinology and metabolism. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
1 author.
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Abstract
The prevalence of obesity has increased significantly in the last few years. Addressing obesity needs multifaceted strategy including prevention, accurate diagnosis, treatment of secondary causes, diet and exercise, behavioral changes and long term management. In addition it involves integration of multiple teams including endocrinologist, respiratory medicine, ENT, psychiatry, physiotherapy, diet, and bariatric surgeon. Artificial intelligence can help with each of these aspects by enabling predictive analysis, behavioral intervention in real time and improving patient outcome. There are certain challenges in integrating AI with patient management including ensuring data privacy and mitigating algorithm bias. But overall, it represents a promising tool to empower both the individual and the physician treating obesity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.