Algorithmic fairness in artificial intelligence for medicine and healthcare

RJ Chen, JJ Wang, DFK Williamson, TY Chen… - Nature biomedical …, 2023 - nature.com
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …

A review on fairness in machine learning

D Pessach, E Shmueli - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …

Preparing medical imaging data for machine learning

MJ Willemink, WA Koszek, C Hardell, J Wu… - Radiology, 2020 - pubs.rsna.org
Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The
potential applications are vast and include the entirety of the medical imaging life cycle from …

Sybil: a validated deep learning model to predict future lung cancer risk from a single low-dose chest computed tomography

PG Mikhael, J Wohlwend, A Yala, L Karstens… - Journal of Clinical …, 2023 - ascopubs.org
PURPOSE Low-dose computed tomography (LDCT) for lung cancer screening is effective,
although most eligible people are not being screened. Tools that provide personalized …

Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks

J Yao, X Zhu, J Jonnagaddala, N Hawkins… - Medical Image Analysis, 2020 - Elsevier
Traditional image-based survival prediction models rely on discriminative patch labeling
which make those methods not scalable to extend to large datasets. Recent studies have …

Non–small cell lung cancer: epidemiology, screening, diagnosis, and treatment

N Duma, R Santana-Davila, JR Molina - Mayo Clinic Proceedings, 2019 - Elsevier
Lung cancer remains the leading cause of cancer deaths in the United States. In the past
decade, significant advances have been made in the science of non–small cell lung cancer …

NCCN guidelines® insights: lung cancer screening, version 1.2022: featured updates to the NCCN guidelines

DE Wood, EA Kazerooni, D Aberle, A Berman… - Journal of the National …, 2022 - jnccn.org
The NCCN Guidelines for Lung Cancer Screening recommend criteria for selecting
individuals for screening and provide recommendations for evaluation and follow-up of lung …

Lung cancer screening, version 3.2018, NCCN clinical practice guidelines in oncology

DE Wood, EA Kazerooni, SL Baum, GA Eapen… - Journal of the National …, 2018 - jnccn.org
Lung cancer is the leading cause of cancer-related mortality in the United States and
worldwide. Early detection of lung cancer is an important opportunity for decreasing …

[HTML][HTML] Lung cancer incidence and mortality with extended follow-up in the National Lung Screening Trial

National Lung Screening Trial Research Team - Journal of Thoracic …, 2019 - Elsevier
Abstract Introduction The National Lung Screening Trial (NLST) randomized high-risk
current and former smokers to three annual screens with either low-dose computed …

Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures

RTHM Larue, G Defraene… - The British journal of …, 2017 - academic.oup.com
Quantitative analysis of tumour characteristics based on medical imaging is an emerging
field of research. In recent years, quantitative imaging features derived from CT, positron …