Machine learning predictive models in neurosurgery: an appraisal based on the TRIPOD guidelines. Systematic review
OBJECTIVE In recent years, machine learning models for clinical prediction have become
increasingly prevalent in the neurosurgical literature. However, little is known about the …
increasingly prevalent in the neurosurgical literature. However, little is known about the …
Research using the Quality Outcomes Database: accomplishments and future steps toward higher-quality real-world evidence
AL Asher, RW Haid, AR Stroink… - Journal of …, 2023 - thejns.org
OBJECTIVE The Quality Outcomes Database (QOD) was established in 2012 by the
NeuroPoint Alliance, a nonprofit organization supported by the American Association of …
NeuroPoint Alliance, a nonprofit organization supported by the American Association of …
Leveraging machine learning to ascertain the implications of preoperative body mass index on surgical outcomes for 282 patients with preoperative obesity and …
OBJECTIVE Prior studies have revealed that a body mass index (BMI)≥ 30 is associated
with worse outcomes following surgical intervention in grade 1 lumbar spondylolisthesis …
with worse outcomes following surgical intervention in grade 1 lumbar spondylolisthesis …
Impact of educational background on preoperative disease severity and postoperative outcomes among patients with lumbar spondylolisthesis: a Quality Outcomes …
OBJECTIVE Deficiency in patient education has been correlated with increased disease-
related morbidity and decreased access to care. However, the associations between …
related morbidity and decreased access to care. However, the associations between …
Predictors of patient satisfaction after surgery for grade 1 degenerative spondylolisthesis: a 5-year analysis of the Quality Outcomes Database: Presented at the 2024 …
OBJECTIVE Lumbar decompression and/or fusion surgery is a common operation for
symptomatic lumbar spondylolisthesis refractory to conservative management. Multiyear …
symptomatic lumbar spondylolisthesis refractory to conservative management. Multiyear …
A new classification and laparoscopic treatment of extrahepatic choledochal cyst
M Tao, X Wang, J Han, L Cao, J Li, S Zheng - Clinics and Research in …, 2024 - Elsevier
Background Prior ty** methods fail to provide predictive insights into surgical complexities
for extrahepatic choledochal cyst (ECC). This study aims to establish a new classification …
for extrahepatic choledochal cyst (ECC). This study aims to establish a new classification …
[HTML][HTML] Has artificial intelligence in spine surgery lived up to the hype? A narrative review of recent approaches, current challenges, and the path forward
Healthcare applications of artificial intelligence (AI) and machine learning (ML) are currently
in a stage of exponential growth; however, their adoption into clinical practice across clinical …
in a stage of exponential growth; however, their adoption into clinical practice across clinical …
Connectomic insight into unique stroke patient recovery after rTMS treatment
R Chen, NB Dadario, B Cook, L Sun, X Wang… - Frontiers in …, 2023 - frontiersin.org
An improved understanding of the neuroplastic potential of the brain has allowed
advancements in neuromodulatory treatments for acute stroke patients. However, there …
advancements in neuromodulatory treatments for acute stroke patients. However, there …
Machine learning and lumbar spondylolisthesis
While lumbar spondylolisthesis is one of the most common conditions cared for by spine
surgeons, there remains limited evidence guiding its diagnosis, classification, and …
surgeons, there remains limited evidence guiding its diagnosis, classification, and …
Clinical Databases in Spine Surgery: Strength in Numbers
Since the 21st Century Cures Act, real-world research has been increasingly valued as a
source of evidence to guide clinical practice. 1 Randomized control trials (RCTs) constitute …
source of evidence to guide clinical practice. 1 Randomized control trials (RCTs) constitute …