Physician recommendation based on limited information

What is it about?

Guiding patients to hospitals that can serve their treatment needs both timely and with good quality can make the best use of precious medical resources. In this article, we propose a novel diversity-enhanced hierarchical physician recommendation approach to address this issue. We adopt matrix factorization to estimate physician competency and exploit implicit similarity relationships to improve the competency estimation of physicians that we are of little information of. We then balance the patient preference and physician diversity using two novel heuristic algorithms.

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Photo by National Cancer Institute on Unsplash

Photo by National Cancer Institute on Unsplash

Why is it important?

We propose to adopt matrix factorization (MF) to compute physician competency. By exploiting the implicit similarity relationship, we effectively estimate the competency of physicians that we are of little information of. We recommend capable hospitals and physicians with improved diversity such that we not only improve the utilization of medical resources but also confidently satisfy patient requirements.