Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Similarity analysis of patients' data: Bangladesh perspective
Health data integration with Secured Record Linkage: A practical solution for Bangladesh and other developing countries
Similarity Measures for Categorical Data: A Comparative Evaluation
A Novel Similarity Measure for Clustering Categorical Data Sets
Interpretability and Informativeness of Clustering Methods for Exploratory Analysis of Clinical Data
Data mining techniques in Indian healthcare: A short review
MLBCD: a machine learning tool for big clinical data
“You Get Reminded You’re a Sick Person”: Personal Data Tracking and Patients With Multiple Chronic Conditions
Using Rules to Analyse Bio-medical Data: A Comparison between C4.5 and PCL
Binary Similarity Detection Using Machine Learning
Temporal pattern discovery in longitudinal electronic patient records
Statistical Analysis of Big Data on Pharmacogenomics
Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data
Identifying factors influencing contraceptive use in Bangladesh: evidence from BDHS 2014 data
Semantic similarity in the biomedical domain: an evaluation across knowledge sources
Breast Cancer Diagnosis Via Data Mining: Performance Analysis of Seven Different Algorithms
Bigdata analysis and comparison of bigdata analytic approches
Big data in health care: using analytics to identify and manage high-risk and high-cost patients.
Analysis of Different Similarity Measure Functions and their Impacts on Shared Nearest Neighbor Clustering Approach
A Measure of Similarity of Time Series Containing Missing Data Using the Mahalanobis Distance
Big Data Analysis in Healthcare
Automatic record linkage using seeded nearest neighbour and support vector machine classification
A muscle-driven approach to restore stepping with an exoskeleton for individuals with paraplegia
What are the Gaps in Mobile Patient Portal? Mining Users Feedback Using Topic Modeling
An unsupervised object-level image segmentation method based on foreground and background priors
on computing minimal correction subsets .