7 citations · 16 across the 6 of their papers we have counts for
6 papers
Beyond Negation Detection: Comprehensive Assertion Detection Models for Clinical NLP
Veysel Kocaman, Yigit Gul, M. Aytug Kaya +4
Assertion status detection is a critical yet often overlooked component of clinical NLP, essential for accurately attributing extracted medical facts. Past studies have narrowly fo…
Beyond Accuracy: Automated De-Identification of Large Real-World Clinical Text Datasets
Veysel Kocaman, Hasham Ul Haq, David Talby
Recent research advances achieve human-level accuracy for de-identifying free-text clinical notes on research datasets, but gaps remain in reproducing this in large real-world sett…
Understanding COVID-19 News Coverage using Medical NLP
Ali Emre Varol, Veysel Kocaman, Hasham Ul Haq +1
Being a global pandemic, the COVID-19 outbreak received global media attention. In this study, we analyze news publications from CNN and The Guardian - two of the world's most infl…
Mining Adverse Drug Reactions from Unstructured Mediums at Scale
Hasham Ul Haq, Veysel Kocaman, David Talby
Adverse drug reactions / events (ADR/ADE) have a major impact on patient health and health care costs. Detecting ADR's as early as possible and sharing them with regulators, pharma…
Deeper Clinical Document Understanding Using Relation Extraction
Hasham Ul Haq, Veysel Kocaman, David Talby
The surging amount of biomedical literature & digital clinical records presents a growing need for text mining techniques that can not only identify but also semantically relate en…
Intelligent EHRs: Predicting Procedure Codes From Diagnosis Codes
Hasham Ul Haq, Rameel Ahmad, Sibt Ul Hussain
In order to submit a claim to insurance companies, a doctor needs to code a patient encounter with both the diagnosis (ICDs) and procedures performed (CPTs) in an Electronic Health…