EcoSupply: a machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics

A global supply chain spans several regions and countries across the globe. A tremendous spurt in the extent of globalization has necessitated the need for modeling global supply chains in place of the conventional supply chains. In this paper, we propose a framework, EcoSupply, to analyze the supply chain ecosystem in a probabilistic setting unlike the existing methodologies, which presume a deterministic context. EcoSupply keeps track of the previous observations in order to facilitate improved prediction about the influence of uncertainties in the ecosystem, and provides a coherent mathematical exposition to construe the new associations, among the different supply chain stakeholders, in place of the existing links. To the best of our knowledge, EcoSupply is the first machine learning based paradigm to incorporate the dynamics of global supply chains

Gallbladder reporting and data system (GB-RADS) for risk stratification of gallbladder wall thickening on ultrasonography:an international expert consensus

The Gallbladder Reporting and Data System (GB-RADS) ultrasound (US) risk stratification is proposed to improve consistency in US interpretations, reporting, and assessment of risk of malignancy in gallbladder wall thickening in non-acute setting. It was developed based on a systematic review of the literature and the consensus of an international multidisciplinary committee comprising expert radiologists, gastroenterologists, gastrointestinal surgeons, surgical oncologists, medical oncologists, and pathologists using modified Delphi method. For risk stratification, the GB-RADS system recommends six categories (GB-RADS 0–5) of gallbladder wall thickening with gradually increasing risk of malignancy. GB-RADS is based on gallbladder wall features on US including symmetry and extent (focal vs. circumferential) of involvement, layered appearance, intramural features (including intramural cysts and echogenic foci), and interface with the liver. GB-RADS represents the first collaborative effort at risk stratifying the gallbladder wall thickening. This concept is in line with the other US-based risk stratification systems which have been shown to increase the accuracy of detection of malignant lesions and improve management. Graphical abstract: [Figure not available: see fulltext.]