Scientific Publications

Manuscripts

Patient Perspectives on the Ethical Implementation of a Rapid Learning System for Oncology Care

Journal of Oncology Practice
A rapid learning system (RLS) of health care harnesses data generated from routine patient care to create a virtuous cycle of data collection and…

Qualitative Study of Oncologists’ Views on the CancerLinQ Rapid Learning System

JCO Oncology Practice
Mayo et al.

Building a Rapid Learning Health Care System for Oncology: Why CancerLinQ Collects Identifiable Health Information to Achieve Its Vision

Journal of Clinical Oncology
Shah et al.

Building a Rapid Learning Health Care System for Oncology: The Regulatory Framework of CancerLinQ

Journal of Clinical Oncology
Schilsky et al.

Abstracts

Trends in immunotherapy use in patients with advanced non-small cell lung cancer (aNSCLC) patients: Analysis of real-world data

2020 ASCO Virtual Scientific Program
Kushi et al.

Low rates of BRCA1 and BRCA2 testing for patients with ovarian cancer in ASCO's CancerLinQ, a real-world database

2020 ASCO Virtual Scientific Program
Dewdney et al.

Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: A machine learning approach

2020 ASCO Virtual Scientific Program
Dreyfus et al.

Vital status ascertainment in cancerlinq discovery (CLQD): Improvement in mortality capture with a supplemental data source

2020 ASCO Virtual Scientific Program
Potter et al.

Overall survival (OS) in advanced non-small cell lung cancer (aNSCLC) patients treated with frontline chemotherapy or immunotherapy by comorbidity: A…

2020 ASCO Virtual Scientific Program
Rivera et al.

Annual trends in opioid prescribing for patients (Pts) with metastatic non-small cell lung cancer (mNSCLC): Cancerlinq data analysis, 2010 to 2017

2020 ASCO Virtual Scientific Program
Paice et al.

Development of an algorithm using natural language processing to identify metastatic breast cancer patients from clinical notes.

2020 ASCO Virtual Scientific Program
Swaminathan et al.

Machine learning imputation of Eastern Cooperative Oncology Group performance status (ECOG PS) scores from data in CancerLinQ discovery

2020 ASCO Virtual Scientific Program
Agrawal et al.

Artificial intelligence model to predict slow progression for advanced non-small cell lung cancer (aNSCLC) patients receiving second-line therapies

2020 ASCO Virtual Scientific Program
Charest et al.