Data Driven Analytics for Personalized Healthcare

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Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation (2018, methodology): “Several patternbased methods generate recommendations by utilizing the similarity of patients [15, 33, 40], but they are challenging to directly learn the relation between patients and medications.”
Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence (2019, background): “In the current digital age, the electronic health record (EHR) represents a massive repository of electronic data points representing a diverse array of clinical information 1–3 .”
Personalized Prescription for Comorbidity (2018, methodology): “Prescription settled by pattern-based methods is to identify the treatments based on the similarities among records of patients [9,10,21].”
A Review of the Role of Artificial Intelligence in Healthcare (2023, background): “Additionally, accumulated data from multiple sources, such as health information systems (HISs), wearable devices, telemedicine, mHealth, telehealth, MIDs, and other AI-powered medical technology [44], create big data that accelerate the utilization of ML and AI in health systems using the learning ”