21 November 2018
Emergency admissions are a major source of healthcare spending. This research paper aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. It found that that standard machine learning models not only outperformed the best statistical model but they did so with a substantially better performance and calibration.
Turning a groundswell of climate action into ground rules for net zero
Challenges and opportunities in translating ethical AI principles into practice for children
High Molar Mass Polycarbonates as Closed-Loop Recyclable Thermoplastics
Accelerating carbon neutrality in China: Sensitive intervention points for the energy and transport sectors in Beijing and Hong Kong
School to work transition: Employment and expectations of former madrasa students in Cox’s Bazar, Bangladesh
Prosocial preferences improve climate risk management in subsistence farming communities
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