Objective: This study aimed to evaluate local control (LC) of tumors, patient overall survival (OS), and the safety of stereotactic radiosurgery (SRS) for esophageal cancer brain metastases (EBMs).
Methods: This retrospective cohort study used data from 15 International Radiosurgery Research Foundation facilities encompassing 67 patients with 185 EBMs managed using SRS between January 2000 and May 2022. The median patient age was 63 years, with a male predominance (92.
Objective: The Pfirrmann scoring system classifies lumbosacral disc degeneration based on magnetic resonance imaging signal intensity. The relationship between pre-existing disc degeneration and patient-reported outcome measures (PROMs) after one-level lumbar fusion is not well documented. The purpose of this study was to investigate the relationship between the severity of preoperative intervertebral disc degeneration and preoperative and postoperative PROMs in patients undergoing one-level lumbar fusion.
View Article and Find Full Text PDFObjective: The goal of this study was to characterize local tumor control (LC), overall survival (OS), and safety of stereotactic radiosurgery for colorectal brain metastasis (CRBM).
Methods: Ten international institutions participating in the International Radiosurgery Research Foundation provided data for this retrospective case series. This study included 187 patients with CRBM (281 tumors), with a median age of 62 years and 56.
Background: There are limited data regarding outcomes for patients with gastrointestinal (GI) primaries and brain metastases treated with stereotactic radiosurgery (SRS).
Objective: To examine clinical outcomes after SRS for patients with brain metastases from GI primaries and evaluate potential prognostic factors.
Methods: The International Radiosurgery Research Foundation centers were queried for patients with brain metastases from GI primaries managed with SRS.
J Biomed Inform
August 2018
In the past, algorithms exploiting varying semantics in interactions between biological objects such as genes and diseases have been used in bioinformatics to uncover latent relationships within biological datasets. In this paper, we consider the algorithm Medusa in parallel with binary classification in order to find potential compounds to inhibit oral cancer. Oral cancer affects the mouth and pharynx and has a high mortality rate due to its late discovery.
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