28 citations · 48 across the 8 of their papers we have counts for
8 papers
A Hybrid Citation Retrieval Algorithm for Evidence-based Clinical Knowledge Summarization: Combining Concept Extraction, Vector Similarity and Query Expansion for High Precision
Kalpana Raja, Andrew J Sauer, Ravi P Garg +2
Novel information retrieval methods to identify citations relevant to a clinical topic can overcome the knowledge gap existing between the primary literature (MEDLINE) and online c…
An Information Extraction Approach to Prescreen Heart Failure Patients for Clinical Trials
Abhishek Kalyan Adupa, Ravi Prakash Garg, Jessica Corona-Cox +2
To reduce the large amount of time spent screening, identifying, and recruiting patients into clinical trials, we need prescreening systems that are able to automate the data extra…
CRTS: A type system for representing clinical recommendations
Ravi P Garg, Kalpana Raja, Siddhartha R Jonnalagadda
Background: Clinical guidelines and recommendations are the driving wheels of the evidence-based medicine (EBM) paradigm, but these are available primarily as unstructured text and…
A Bootstrap Machine Learning Approach to Identify Rare Disease Patients from Electronic Health Records
Ravi Garg, Shu Dong, Sanjiv Shah +1
Rare diseases are very difficult to identify among large number of other possible diagnoses. Better availability of patient data and improvement in machine learning algorithms empo…
Using Natural Language Processing to Screen Patients with Active Heart Failure: An Exploration for Hospital-wide Surveillance
Shu Dong, R Kannan Mutharasan, Siddhartha Jonnalagadda
In this paper, we proposed two different approaches, a rule-based approach and a machine-learning based approach, to identify active heart failure cases automatically by analyzing…
Automatically extracting, ranking and visually summarizing the treatments for a disease
Prakash Reddy Putta, John J. Dzak, Siddhartha R. Jonnalagadda
Clinicians are expected to have up-to-date and broad knowledge of disease treatment options for a patient. Online health knowledge resources contain a wealth of information. Howeve…