Preoperative Statistical Models to Predict Success of Endoscopic Sleeve Gastroplasty at 1 Year: Retrospective Study on 200 Patients in a Single Centre

Vannucci, Maria; Niyishaka, Patrick; Collins, Toby; Mascagni, Pietro; Luna, Maria R. Rodriguez; Hostettler, Alexandre; Dallemagne, Bernard; Perretta, Silvana

doi:10.1016/j.gie.2022.04.643

Cited by 1 publication

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“…This scenario underscores the urgent need for innovative approaches in predicting and managing obesity [27][28][29][30]. The necessity for new predictive methods in combating obesity is driven by the need to tailor interventions to individual characteristics and circumstances [31][32][33][34][35]. Current approaches typically employ one-size-fits-all strategies that do not account for the complex interplay of genetic, environmental, and personal factors that influence obesity [36,37].…”

Section: Discussionmentioning

confidence: 99%

Chronic Diseases: A Comprehensive Review of Applications for Prediction of Obesity

A Huang

2024

IOD

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Recent advancements in ML have opened new avenues for addressing complex health issues by facilitating personalized medicine, predictive diagnostics, and behaviour modification strategies. In the context of obesity, ML algorithms can analyse vast datasets-from genetic predispositions to behavioural and environmental factors-enabling the development of tailored intervention strategies that are more adaptive and responsive to individual needs [9,10]. Moreover, ML can enhance the real-time monitoring and management of obesity through wearable technology and mobile applications, offering immediate feedback and support to individuals as they navigate their daily choices [11,12]. The integration of ML into obesity research and management is not without challenges [13,14]. Issues such as data privacy, algorithmic bias, and the digital divide pose significant barriers to the widespread adoption of these technologies [7,15]. Moreover, the effectiveness of ML-driven interventions must be scrutinized through rigorous, multidisciplinary research to ensure they deliver

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Section: Discussionmentioning

confidence: 99%

Chronic Diseases: A Comprehensive Review of Applications for Prediction of Obesity

A Huang

2024

IOD

View full text Add to dashboard Cite

show abstract

Preoperative Statistical Models to Predict Success of Endoscopic Sleeve Gastroplasty at 1 Year: Retrospective Study on 200 Patients in a Single Centre

Cited by 1 publication

References 0 publications

Chronic Diseases: A Comprehensive Review of Applications for Prediction of Obesity

Chronic Diseases: A Comprehensive Review of Applications for Prediction of Obesity

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