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

Disproportionate impact of COVID-19 disease among racial and ethnic minorities in the U.S. cancer population as seen in CancerLinQ Discovery data.

2020 ASCO Quality Care Symposium
Potter et al.

Impact of curated data on electronic quality eeasure capture rates within CancerLinQ

2020 ASCO Quality Care Symposium
Rios et al.

The relationship between treatment intensity and characteristics of patients with early stage breast cancer

2020 ASCO Quality Care Symposium
Franks et al.

Development of an artificial intelligence model to dynamically predict metastatic recurrence of early-stage breast cancer patients

2020 ASCO Virtual Scientific Program
Vaidya et al.

Identification of transgender people with cancer in electronic health records (EHR): Recommendations based on CancerLinQ observations

2020 ASCO Virtual Scientific Program
Alpert et al.

Treatment trends with immune checkpoint inhibitor (ICI) therapy in older adults with lung cancer

2020 ASCO Virtual Scientific Program
Walko et al.

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.