AI Tool Discerns Lung Cancer Outcomes From Imaging Reports
Deep natural language processing may be able to estimate the presence of active cancer, cancer worsening or progression, and cancer improvement or response from radiologic reports.
Deep natural language processing may be able to estimate the presence of active cancer, cancer worsening or progression, and cancer improvement or response from radiologic reports.
Among individuals across the spectrum of lung cancer risk, efforts are needed to improve physician-patient discussion about lung cancer screening.
An informational film can improve knowledge and reduce decisional conflict for individuals considering participating in lung cancer screening.
Humans are used to seeing canines used as tools in forensics — their skills are often harnessed to smell out drugs or trail a criminal. Some dogs are even used to locate household pests. The use of canines to detect lung cancer from smell alone, however, is a new prospect for oncologists and their patients.
In a retrospective study conducted in the United States and the United Kingdom, researchers evaluated the prescribing of preventative medications in patients with lung cancer discharged from hospital at the end of life.
Patients in higher quintiles of lung cancer risk had significantly more diagnoses of lung cancer.
Risk-based criteria would screen high-risk smokers currently ineligible for screening using USPSTF criteria, resulting in more modest decreases in lung cancer screening.
Patient knowledge of eligibility criteria, benefits and harms of screening was improved.
The American Cancer Society says that such testing could cut mortality rate by 20%.
Significant prognostic factors include four factors from earlier index, as well as EGFR and ALK alterations.