This study demonstrated that the concurrent use of this new artificial intelligence tool alongside mammography improved the diagnostic performance of radiologists in the detection of breast cancer without prolonging their workflow.
This study found that abbreviated breast magnetic resonance imaging as a supplemental screening test in women with dense breasts shows an increase in cancer detection over digital breast tomosynthesis screening.
“This algorithm could allow us a better shot at personalized medicine and enhance our ability to tailor the treatments to be as appropriate as possible,” said study author Daniel Chang, MD.
The chief executive officer and co-founder of TrialJectory spoke about the online tool and what it offers for patients, providers, and pharmaceutical companies.
This study created and assessed a parsimonious radiomic model that was able to identify a vulnerable subset of screen-detected lung cancers that are associated with poor outcome.
In this study, investigators found that the hydrogel spacer has a favorable risk-benefit profile for patients receiving radiotherapy for prostate cancer.
The deep learning survival neural network model demonstrated the potential to provide personalized treatment recommendations based on real clinical data in patients with non-small cell lung cancer.
Cellectar opens manufacturing facility for radiolabeled CLR1404
MRI has outrun other modalities in a screening trial involving high-risk women. Such research helps justify an estimated $1.4 billion a year in direct costs for the United States if new American Cancer Society guidelines
Breast MRI identifies mammographically occult secondary tumors in about 6% of women with early-stage breast cancer who would otherwise qualify for partial breast irradiation