The Convergence of Human and Artificial Intelligence on Clinical Care - Part II

Dear Colleagues,

Given the enormous success of the Part I issue (The Convergence of Human and Artificial Intelligence on Clinical Care - Part I), I am thrilled to move forward to Special Issue Part II. Briefly, Part I was a successful collection not only because of the quality of the articles but also because of the range of AI applications in healthcare. Briefly, Part I of the collection contains 12 studies, large and pilots, that try to tackle the changing landscape of healthcare using AI. The articles are in five main areas: (i) using adaptive imputation to increase the density of clinical data for improving downstream modeling, (ii) machine learning-empowered diagnosis models, (iii) machine learning models for outcome prediction, (iv) innovative use of AI to improve our understanding of the public view, and (v) understanding of the attitude of providers in trusting insights from AI for complex cases. Overall, studies used an array of data modalities, including data from electronic health records, imaging data, voice signals, resource utilization, Twitter data, and questionnaire, in addition to a wide range of modeling frameworks, designs, and algorithms. 

In Part II, we are focusing not only on methodological advances for diverse data types but also on the implementation component. We particularly welcome articles providing new insights into (i) the ethical and technological challenges when integrating AI into the clinical workflow; (ii) effectiveness and clinical value of tools and AI-enabled decision support systems for improving care; (iii) different ways that AI can be used to improve access, reduce health disparity, and improve outcome; and finally, (iv) other application of AI in pre-clinical and clinical settings, including but not limited to leveraging AI for improving clinical trials among others. We welcome both solicited and unsolicited submissions that will contribute to this goal.

Dr. Vida Abedi
Guest Editor

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