A5041213130- Shoulder Injury and Treatment
- Machine Learning in Healthcare
- Shoulder and Clavicle Injuries
- Breast Cancer Treatment Studies
- AI in cancer detection
- Congenital limb and hand anomalies
- Bone Tumor Diagnosis and Treatments
- Radiomics and Machine Learning in Medical Imaging
- Palliative Care and End-of-Life Issues
- Cancer survivorship and care
- Bone fractures and treatments
- Frailty in Older Adults
- Pulmonary Hypertension Research and Treatments
SUNY Downstate Health Sciences University
2022-2025
State University of New York
2022
Maimonides Medical Center
2022
There are significant disparities in outcomes at the end-of-life (EOL) for minoritized patients with advanced cancer, most dying without a documented serious illness conversation (SIC). This study aims to assess clinician perceptions of utility and challenges implementing machine learning model (ALERT) predict 6-month mortality among solid cancers prompt timely SIC. One-on-one semi-structured interviews were conducted oncology physicians, practice providers, registered nurses, social workers...
189 Background: Machine learning (ML) models can predict mortality and guide end-of-life (EOL) care for patients with advanced solid cancers. Early planning (ACP) leads to more goal-concordant care, yet many patients, especially from minoritized groups, do not engage in serious illness conversations (SIC). Reasons delay include inability of oncologists identify at high short-term risk, uncertainties about prognosis. While ML may improve prognosis accuracy, research on its use impact racial...
590 Background: ML-based mortality prediction tools in oncology can optimize clinical decisions and prompt end-of-life care discussions. Patients with advanced cancer who have engaged Goals of Care (GoC) conversations report improved quality life better alignment. However, oncologists often overly optimistic prognoses miss timely GoC Clinical notes are a valuable source information, but processing extracting data from them is time-consuming labor-intensive. To address this issue, we...