4.1 Article

A supervised machine-learning algorithm predicts intraoperative CSF leak in endoscopic transsphenoidal surgery for pituitary adenomas

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Clinical Neurology

Pituitary Tumors in the Computational Era, Exploring Novel Approaches to Diagnosis, and Outcome Prediction with Machine Learning

Sauson Soldozy et al.

Summary: Machine learning has become an essential asset in pituitary surgery, with radiomics and artificial neural networks being the main focus of applications. These methods can be used for diagnosis, predicting intraoperative changes, tumor aggressiveness, and other factors related to patient outcomes.

WORLD NEUROSURGERY (2021)

Review Computer Science, Artificial Intelligence

The impact of machine learning on patient care: A systematic review

David Ben-Israel et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)

Article Clinical Neurology

Attitudes of Patients and Their Relatives Toward Artificial Intelligence in Neurosurgery

Paolo Palmisciano et al.

WORLD NEUROSURGERY (2020)

Article Clinical Neurology

Machine learning in neurosurgery: a global survey

Victor E. Staartjes et al.

ACTA NEUROCHIRURGICA (2020)

Article Biochemical Research Methods

Evaluation of variable selection methods for random forests and omics data sets

Frauke Degenhardt et al.

BRIEFINGS IN BIOINFORMATICS (2019)

Article Computer Science, Theory & Methods

Efficient Hyperparameter Tuning with Grid Search for Text Categorization using kNN Approach with BM25 Similarity

Raji Ghawi et al.

OPEN COMPUTER SCIENCE (2019)

Article Computer Science, Information Systems

Trusting telemedicine: A discussion on risks, safety, legal implications and liability of involved stakeholders

E. Parimbelli et al.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2018)

Article Otorhinolaryngology

Factors impacting cerebrospinal fluid leak rates in endoscopic sellar surgery

Tom T. Karnezis et al.

INTERNATIONAL FORUM OF ALLERGY & RHINOLOGY (2016)

Article Mathematical & Computational Biology

Identifying representative trees from ensembles

Mousumi Banerjee et al.

STATISTICS IN MEDICINE (2012)

Article Computer Science, Artificial Intelligence

Spatial regularization of SVM for the detection of diffusion alterations associated with stroke outcome

Remi Cuingnet et al.

MEDICAL IMAGE ANALYSIS (2011)

Article Computer Science, Software Engineering

Boruta - A System for Feature Selection

Miron B. Kursa et al.

FUNDAMENTA INFORMATICAE (2010)

Article Clinical Neurology

Endoscopic pituitary surgery: a systematic review and meta-analysis Clinical article

Abtin Tabaee et al.

JOURNAL OF NEUROSURGERY (2009)

Article Clinical Neurology

Risk factors of cerebrospinal fluid rhinorrhea following transsphenoidal surgery

H Nishioka et al.

ACTA NEUROCHIRURGICA (2005)

Article Medicine, Research & Experimental

Incidence, etiology, and management of cerebrospinal fluid leaks following trans-sphenoidal surgery

SG Shiley et al.

LARYNGOSCOPE (2003)

Article Computer Science, Artificial Intelligence

Benchmarking attribute selection techniques for discrete class data mining

MA Hall et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2003)

Review Computer Science, Artificial Intelligence

A review of evidence of health benefit from artificial neural networks in medical intervention

PJG Lisboa

NEURAL NETWORKS (2002)

Review Critical Care Medicine

Artificial intelligence applications in the intensive care unit

CW Hanson et al.

CRITICAL CARE MEDICINE (2001)