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The growing demand for key healthcare resources such as clinical expertiseand facilities has motivated the emergence of artificial intelligence (AI)based decision support systems. We address the problem of predicting clinicalworkups for specialty referrals. As an alternative for manually-createdclinical checklists, we propose a data-driven model that recommends thenecessary set of diagnostic procedures based on the patients' most recentclinical record extracted from the Electronic Health Record (EHR). This has thepotential to enable health systems expand timely access to initial medicalspecialty diagnostic workups for patients. The proposed approach is based on anensemble of feed-forward neural networks and achieves significantly higheraccuracy compared to the conventional clinical checklists.

Clinical Recommender System: Predicting Medical Specialty Diagnostic Choices with Neural Network Ensembles