Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review.
Seyed Farzad MaroufiYücel DoğruelAhmad Pour-RashidiGurkirat S KohliColson Tomberlin ParkerTatsuya UchidaMohamed Z AsfourClara MartinMariagrazia NizzolaAlessandro De BonisMamdouh Tawfik-HelikaAmin TavallaiAaron A Cohen-GadolPaolo PalmiscianoPublished in: Pituitary (2024)
AI/ML modeling holds promise for improving pituitary adenoma surgery by enhancing preoperative planning and optimizing surgical strategies. However, addressing challenges such as algorithm selection, performance evaluation, data heterogeneity, and ethics is essential to establish robust and reliable ML models that can revolutionize neurosurgical practice and benefit patients.
Keyphrases
- artificial intelligence
- big data
- machine learning
- deep learning
- minimally invasive
- coronary artery bypass
- end stage renal disease
- current status
- newly diagnosed
- chronic kidney disease
- healthcare
- ejection fraction
- peritoneal dialysis
- patients undergoing
- primary care
- single cell
- electronic health record
- quality improvement
- atrial fibrillation
- data analysis
- percutaneous coronary intervention