AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Pituitary Neoplasms

Showing 21 to 30 of 61 articles

Clear Filters

A multi-task two-path deep learning system for predicting the invasiveness of craniopharyngioma.

Computer methods and programs in biomedicine 35104686
BACKGROUND AND OBJECTIVE: Craniopharyngioma is a kind of benign brain tumor in histography. However, it might be clinically aggressive and have severe manifestations, such as increased intracranial pressure, hypothalamic-pituitary dysfunction, and vi...
Craniopharyngioma Deep Learning Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Pituitary Neoplasms Reproducibility of Results
View on PubMed DOI

Machine Learning-Based Analysis and Prediction of Unplanned 30-Day Readmissions After Pituitary Adenoma Resection: A Multi-Institutional Retrospective Study With External Validation.

Neurosurgery 35384923
BACKGROUND: Unplanned readmission after transsphenoidal resection of pituitary adenoma can occur in up to 10% of patients but is unpredictable.
Adenoma Bayes Theorem Humans Machine Learning Patient Readmission Pituitary Neoplasms Predictive Value of Tests Retrospective Studies
View on PubMed DOI

Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study.

Clinical neurology and neurosurgery 35662054
OBJECTIVES: Ki67 is an important biomarker of pituitary adenoma (PA) aggressiveness. In this study, PA invasion of surrounding structures is investigated and deep learning (DL) models are established for preoperative prediction of Ki67 labeling index...
Adenoma Deep Learning Humans Ki-67 Antigen Magnetic Resonance Imaging Pituitary Neoplasms Retrospective Studies
View on PubMed DOI

Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network.

European radiology 36396792
OBJECTIVES: To develop a U-Net-based deep learning model for automated segmentation of craniopharyngioma.
Craniopharyngioma Deep Learning Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Pituitary Neoplasms
View on PubMed DOI

Deep learning-based image reconstruction improves radiologic evaluation of pituitary axis and cavernous sinus invasion in pituitary adenoma.

European journal of radiology 36527773
PURPOSE: To compare performance of 1-mm deep learning reconstruction (DLR) with 3-mm routine MRI imaging for the delineation of pituitary axis and identification of cavernous sinus invasion for pituitary macroadenoma.
Adenoma Cavernous Sinus Deep Learning Female Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Neoplasm Invasiveness Pituitary Diseases Pituitary Neoplasms Retrospective Studies
View on PubMed DOI

MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.

BMC medical informatics and decision making 36691030
BACKGROUND: Detecting brain tumors in their early stages is crucial. Brain tumors are classified by biopsy, which can only be performed through definitive brain surgery. Computational intelligence-oriented techniques can help physicians identify and ...
Brain Neoplasms Deep Learning Glioma Humans Machine Learning Magnetic Resonance Imaging Meningeal Neoplasms Meningioma Pituitary Neoplasms
View on PubMed DOI

Deep learning based identification of pituitary adenoma on surgical endoscopic images: a pilot study.

Neurosurgical review 37910280
Accurate tumor identification during surgical excision is necessary for neurosurgeons to determine the extent of resection without damaging the surrounding tissues. No conventional technologies have achieved reliable performance for pituitary adenoma...
Adenoma Deep Learning Endoscopy Humans Pilot Projects Pituitary Neoplasms Retrospective Studies Treatment Outcome
View on PubMed DOI

Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review.

Pituitary 38183582
PURPOSE: Pituitary adenoma surgery is a complex procedure due to critical adjacent neurovascular structures, variations in size and extensions of the lesions, and potential hormonal imbalances. The integration of artificial intelligence (AI) and mach...
Adenoma Artificial Intelligence Humans Machine Learning Pituitary Neoplasms
View on PubMed DOI

Usefulness of pituitary high-resolution 3D MRI with deep-learning-based reconstruction for perioperative evaluation of pituitary adenomas.

Neuroradiology 38374411
PURPOSE: To evaluate the diagnostic value of T1-weighted 3D fast spin-echo sequence (CUBE) with deep learning-based reconstruction (DLR) for depiction of pituitary adenoma and parasellar regions on contrast-enhanced MRI.
Adenoma Adult Aged Contrast Media Deep Learning Female Humans Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Magnetic Resonance Imaging Male Middle Aged Neoplasm, Residual Pituitary Neoplasms Retrospective Studies
View on PubMed DOI

Unraveling the complexity of the senescence-associated secretory phenotype in adamantinomatous craniopharyngioma using multimodal machine learning analysis.

Neuro-oncology 38334125
BACKGROUND: Cellular senescence can have positive and negative effects on the body, including aiding in damage repair and facilitating tumor growth. Adamantinomatous craniopharyngioma (ACP), the most common pediatric sellar/suprasellar brain tumor, p...
Biomarkers, Tumor Cellular Senescence Child Craniopharyngioma Female Gene Expression Regulation, Neoplastic Humans Machine Learning Male Phenotype Pituitary Neoplasms
View on PubMed DOI
Popular Topics
Recent Journals