A5035374661- Cancer-related molecular mechanisms research
- Radiomics and Machine Learning in Medical Imaging
- Patient-Provider Communication in Healthcare
- Clinical practice guidelines implementation
- Lung Cancer Treatments and Mutations
- Cancer Immunotherapy and Biomarkers
- Health Systems, Economic Evaluations, Quality of Life
- Cancer Genomics and Diagnostics
- Lung Cancer Diagnosis and Treatment
- RNA and protein synthesis mechanisms
- Meta-analysis and systematic reviews
- RNA modifications and cancer
- Lung Cancer Research Studies
- Healthcare cost, quality, practices
Stanford University
2021-2025
Stratford University
2024
Stanford Medicine
2022
Patient-reported outcome measures (PROMs) and patient-reported experience (PREMs) are self-reporting tools that can measure important information about patients, such as health priorities, experience, perception of outcome. The use traditional objective vital signs lab values be supplemented with these self-reported patient to provide a more complete picture patient's status. Machine learning, the computer algorithms improve automatically through is powerful tool in care often does not...
2607 Background: Tumor infiltrating lymphocytes (TIL) are a potential tumor-agnostic biomarker for immune checkpoint inhibitor (ICI) therapy. We previously reported the clinical application of an artificial intelligence-powered spatial TIL analyzer, Lunit SCOPE IO, predicting ICI treatment outcomes in advanced non-small cell lung cancer (NSCLC). Here, we expand IO as across multiple types. Methods: was trained and validated with 2.8 x 10 9 micrometer 2 area 5.9 6 TILs from 3,166 H&E...
512 Background: Machine learning models that predict survival time for patients with cancer can be useful in the clinic. Validating their performance deployment is important but challenging, because only timely source of follow-up/death data electronic medical record (EMR), which known to under-capture deaths resulting informative censoring. We examined whether validation using EMR distinguish between low- and high-quality models, by gold-standard Cancer Registry calculate true model level....
Abstract Blood-based liquid biopsies enable non-invasive characterization of cancers. Cell-free RNA (cfRNA) analysis could potentially complement circulating tumor DNA (ctDNA) and allow broader molecular cancers but has not been extensively explored. Here, we describe RARE-Seq, a novel cfRNA sequencing method designed to maximize sensitivity by targeting rare, tissue-specific transcripts, simultaneously detecting both tumor-derived expression signatures somatic mutations in (ctRNA). To...
<sec> <title>BACKGROUND</title> Patient-reported outcome measures (PROMs) and patient-reported experience (PREMs) are self-reporting tools that can measure important information about patients, such as health priorities, experience, perception of outcome. The use traditional objective vital signs lab values be supplemented with these self-reported patient to provide a more complete picture patient’s status. Machine learning, the computer algorithms improve automatically through is powerful...