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Veerasathpurush Allareddy Sankeerth Rampa Shankar Rengasamy Venugopalan Mohammed H. Elnagar Min Kyeong Lee Maysaa Oubaidin Sumit Yadav 《Orthodontics & craniofacial research》2023,26(Z1):118-123
There is a paucity of largescale collaborative initiatives in orthodontics and craniofacial health. Such nationally representative projects would yield findings that are generalizable. The lack of large-scale collaborative initiatives in the field of orthodontics creates a deficiency in study outcomes that can be applied to the population at large. The objective of this study is to provide a narrative review of potential applications of blockchain technology and federated machine learning to improve collaborative care. We conducted a narrative review of articles published from 2018 to 2023 to provide a high level overview of blockchain technology, federated machine learning, remote monitoring, and genomics and how they can be leveraged together to establish a patient centered model of care. To strengthen the empirical framework for clinical decision making in healthcare, we suggest use of blockchain technology and integrating it with federated machine learning. There are several challenges to adoption of these technologies in the current healthcare ecosystem. Nevertheless, this may be an ideal time to explore how best we can integrate these technologies to deliver high quality personalized care. This article provides an overview of blockchain technology and federated machine learning and how they can be leveraged to initiate collaborative projects that will have the patient at the center of care. 相似文献
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Veerasathpurush Allareddy Maysaa Oubaidin Sankeerth Rampa Shankar Rengasamy Venugopalan Mohammed H. Elnagar Sumit Yadav Min Kyeong Lee 《Orthodontics & craniofacial research》2023,26(Z1):124-130
Machine Learning (ML), a subfield of Artificial Intelligence (AI), is being increasingly used in Orthodontics and craniofacial health for predicting clinical outcomes. Current ML/AI models are prone to accentuate racial disparities. The objective of this narrative review is to provide an overview of how AI/ML models perpetuate racial biases and how we can mitigate this situation. A narrative review of articles published in the medical literature on racial biases and the use of AI/ML models was undertaken. Current AI/ML models are built on homogenous clinical datasets that have a gross underrepresentation of historically disadvantages demographic groups, especially the ethno-racial minorities. The consequence of such AI/ML models is that they perform poorly when deployed on ethno-racial minorities thus further amplifying racial biases. Healthcare providers, policymakers, AI developers and all stakeholders should pay close attention to various steps in the pipeline of building AI/ML models and every effort must be made to establish algorithmic fairness to redress inequities. 相似文献
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Does the interval between prostate biopsy and radical prostatectomy affect the immediate postoperative outcome? 总被引:2,自引:0,他引:2
OBJECTIVE: To determine whether the interval between prostate biopsy and radical prostatectomy (RP) affects the immediate postoperative outcome. PATIENTS AND METHODS: The study was a retrospective chart review of 169 patients who had retropubic RP at our institution. Using a series of univariate and multivariate logistic regression analyses, we evaluated whether the interval between biopsy and RP was a significant independent predictor of operative duration, estimated blood loss, transfusion rate, nerve-sparing (yes/no), positive margin rate, length of stay, complications, and urinary continence after RP. RESULTS: The interval from biopsy to RP was 14-378 days; there were no significant differences in operative duration, estimated intraoperative blood loss, nerve-sparing rate, transfusion rate and amount, hospitalization time, positive margin rate, major postoperative complications, and continence in patients with biopsy to RP intervals above and below the median. The biopsy to RP interval was not an independent predictor of outcomes during or after RP. There were no direct or indirect correlations between biopsy to RP interval and any of the postoperative outcomes. CONCLUSION: The interval between prostate biopsy and retropubic RP appears to have no effect on immediate postoperative outcomes. We were unable to determine a specific minimum required interval beyond 2 weeks after prostate biopsy before proceeding with RP. 相似文献