Health Systems publishes high-quality articles about the
idea that all aspects of health and healthcare delivery can be viewed
from a systems perspective. The journal is moving towards greater
visibility, impact, and reach, not only within the academic community
but also engaging clinicians and healthcare managers in a meaningful
way. To achieve this, there have been several exciting initiatives. One
such initiative is the “Titan Series” .
The Titan Series will spotlight prominent academics in their fields
of Information Systems and Operational Research. The Editors will invite
distinguished scholars to write reflective papers, often taking the
form of authoritative position papers. These papers will revisit and
evaluate previously published work while proposing new directions and
associated synergies leading to innovation.
The inaugural Titan Paper is available here.
Summary:
Title: Beyond mathematics, statistics, and
programming: data science, machine learning, and artificial intelligence
competencies and curricula for clinicians, informaticians, science
journalists, and researchers
Authors: William R. Hersh, Robert E. Hoyt, Steven Chamberlin, Jessica S. Ancker, Aditi Gupta & Tara B. Borlawsky-Payne
Who is this relevant for?
This research discusses strategies for developing curricula that
provide access to data science engaging a variety of stakeholders.
Background
Teaching data science, artificial intelligence in general, or machine
learning approaches typically involves a lot of technical skills, such
as coding or non-standard statistical and mathematical analyses. Hence,
for students with technical background, such courses are more accessible
than for, e.g., healthcare professionals who would like to learn more.
While AI/ML or data science enjoys growing popularity, the technical
details of such courses limit the audience. The authors of this work,
therefore, pose the question how to lower the hurdles for healthcare
professionals who are eager to use such models and methods in practice.
For them, learning the necessary skills and tools would require
different approaches and curricula. This work explores and discusses
such alternative approaches to make AI and the like more accessible to a
variety of stakeholders.