A5070018552- Radiomics and Machine Learning in Medical Imaging
- Colorectal Cancer Surgical Treatments
- Colorectal and Anal Carcinomas
- Colorectal Cancer Screening and Detection
- MRI in cancer diagnosis
- Hepatocellular Carcinoma Treatment and Prognosis
- Gastric Cancer Management and Outcomes
- Colorectal Cancer Treatments and Studies
- Bladder and Urothelial Cancer Treatments
- Esophageal Cancer Research and Treatment
- Sarcoma Diagnosis and Treatment
- Medical Imaging and Analysis
- Frailty in Older Adults
- Prostate Cancer Diagnosis and Treatment
- Anorectal Disease Treatments and Outcomes
- Palliative Care and End-of-Life Issues
- Urinary and Genital Oncology Studies
- Cancer Genomics and Diagnostics
- Cancer Diagnosis and Treatment
- Global Cancer Incidence and Screening
- Cutaneous Melanoma Detection and Management
- Urologic and reproductive health conditions
- Renal cell carcinoma treatment
- Peptidase Inhibition and Analysis
- Testicular diseases and treatments
Memorial Sloan Kettering Cancer Center
2019-2024
Fleury S.A. (Brazil)
2019
Centro Universitário Paulistano
2019
Rectal cancer presents significant diagnostic and therapeutic challenges, with neoadjuvant therapy playing a pivotal role in improving resectability patient outcomes. MRI serves as critical tool assessing treatment response. However, differentiating viable tumor tissue from therapy-induced changes on remains complex task. In this comprehensive review, we explore options for rectal based status, focusing the of guiding decisions. We delve into nuances MRI-based evaluation response following...
e17011 Background: Lymphovascular invasion and embryonal carcinoma predominant (ECP) subtype are the only consistent factors predictive of relapse on active surveillance (AS) in Stage I NSGCT. Current practice guidelines define stage disease by axial dimensions only, despite routine coronal reformations CT images permitting CCNL measurement. was previously reported to be associated with increased risk NSGCT, independent other (Howard et al, 2014). We sought validate this finding through...
11537 Background: Palliative Care Index (PPI) has been proposed to improve the accuracy of survival prediction for advanced cancer patients. The aim this study is investigate feasibility and real-world prognosis oncology inpatients from a Brazilian tertiary hospital using PPI. Methods: Hospitalized patients who have referred Team were enrolled May 2011 December 2018. PPI was collected within 24 hours referral by palliative care physician. Primary endpoint median overall (OS), estimated with...