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Articles 1 - 2 of 2
Full-Text Articles in Management Information Systems
Deploying Machine Learning For A Sustainable Future, Cary Coglianese
Deploying Machine Learning For A Sustainable Future, Cary Coglianese
All Faculty Scholarship
To meet the environmental challenges of a warming planet and an increasingly complex, high tech economy, government must become smarter about how it makes policies and deploys its limited resources. It specifically needs to build a robust capacity to analyze large volumes of environmental and economic data by using machine-learning algorithms to improve regulatory oversight, monitoring, and decision-making. Three challenges can be expected to drive the need for algorithmic environmental governance: more problems, less funding, and growing public demands. This paper explains why algorithmic governance will prove pivotal in meeting these challenges, but it also presents four likely obstacles that …
Analysis Of Massive Online Medical Consultation Service Data To Understand Physicians’ Economic Return: Observational Data Mining Study, Jinglu Jiang, Ann-Frances Cameron, Ming Yang
Analysis Of Massive Online Medical Consultation Service Data To Understand Physicians’ Economic Return: Observational Data Mining Study, Jinglu Jiang, Ann-Frances Cameron, Ming Yang
Management and Accounting Faculty Scholarship
Background: Online health care consultation has become increasingly popular and is considered a potential solution to health care resource shortages and inefficient resource distribution. However, many online medical consultation platforms are struggling to attract and retain patients who are willing to pay, and health care providers on the platform have the additional challenge of standing out in a crowd of physicians who can provide comparable services. Objective: This study used machine learning (ML) approaches to mine massive service data to (1) identify the important features that are associated with patient payment, as opposed to free trial–only appointments; (2) explore the …