Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework

By Nitesh V. Chawla, Darcy A. Davis. 2013

422 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Epidemiology, Health Information Management

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Fei Wang
2. Sanjay Purushotham
3. Yan Liu
4. Zhengping Che
5. Xiao-Jun Zeng
6. Francisco Chiclana
7. Ming Tang
8. Robert Sorrentino

In Epidemiology

1. Fei Wang
2. Robert Sorrentino
3. Ping Zhang
4. Jianying Hu
5. Yan Liu

In Health Information Management

1. Fei Wang
2. Xiao-Jun Zeng
3. Francisco Chiclana
4. Ming Tang
5. Robert Sorrentino
6. Ping Zhang
7. Valerio Persico
8. Huchang Liao

Citations in the corpus

• Distilling Knowledge from Deep Networks with Applications to Healthcare Domain (2015, background): “Recently, there is a growing interest in applying deep learning techniques to computational phenotyping [33] due to the increasing availability of the Electronic Healthcare Records (EHR) and the need for Personalized Healthcare [4, 17].”
• Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics (2014, methodology): “With the right patient similarity in place, patient similarity analytics have been used in the target patient retrieval 14 , medical prognosis 15, 16 , risk stratification 17, 18 , and clinical pathway analysis 19 tasks.”
• Challenges and Opportunities of Big Data in Health Care: A Systematic Review (2016, background): “Along with early detection, big data analytics can also help in the prevention of a wide range of deadly illnesses and personalized disease management and monitoring [5,19,21,22,29,34].”
• A Bibliometric Analysis and Visualization of Medical Big Data Research (2018, background): “Density views are especially useful for understanding the overall structure of a map and drawing attention to the most important areas in the map [9].”
• Interpretable Deep Models for ICU Outcome Prediction (2016, background): “Clinicians are collaborating with computer scientists to improve the state of health care services towards the goal of Personalized Healthcare 2 .”
• The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges (2018, background): “Big data is paving the way to personalized healthcare, both at individual and population level [138, 293, 53].”
• Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0 (2020, background): “personalized healthcare, both at individual and population level [100, 97, 101].”