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The Role of Artificial Intelligence in Predicting Optic Neuritis Subtypes From Ocular Fundus Photographs.
J Neuroophthalmol
December 2024
Division of Ophthalmology (EB-S, AS, AA-A, AS-B, DW, SS, FC), Department of Surgery, University of Calgary, Calgary, Canada; Department of Biomedical Engineering (CN), University of Calgary, Calgary, Canada; Departments of Neurology (LBDL) and Ophthalmology (LBDL), University of Michigan, Ann Arbor, Michigan; and Department of Clinical Neurosciences (SS, FC), University of Calgary, Calgary, Canada.
Background: Optic neuritis (ON) is a complex clinical syndrome that has diverse etiologies and treatments based on its subtypes. Notably, ON associated with multiple sclerosis (MS ON) has a good prognosis for recovery irrespective of treatment, whereas ON associated with other conditions including neuromyelitis optica spectrum disorders or myelin oligodendrocyte glycoprotein antibody-associated disease is often associated with less favorable outcomes. Delay in treatment of these non-MS ON subtypes can lead to irreversible vision loss.
View Article and Find Full Text PDFDevelopment of Predictive Model of Surgical Case Durations Using Machine Learning Approach.
J Med Syst
January 2025
Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
Optimizing operating room (OR) utilization is critical for enhancing hospital management and operational efficiency. Accurate surgical case duration predictions are essential for achieving this optimization. Our study aimed to refine the accuracy of these predictions beyond traditional estimation methods by developing Random Forest models tailored to specific surgical departments.
View Article and Find Full Text PDFStandard: Human gastric organoids.
Cell Regen
January 2025
Guangzhou National Laboratory, Guangzhou, 510005, China.
Organoid technology provides a transformative approach to understand human physiology and pathology, offering valuable insights for scientific research and therapeutic development. Human gastric organoids, in particular, have gained significant interest for applications in disease modeling, drug discovery, and studies of tissue regeneration and homeostasis. However, the lack of standardized quality control has limited their extensive clinical applications.
View Article and Find Full Text PDFMachine learning validation of a simple prediction model for the correlation between advanced age and clinical outcomes in patients with aneurysmal subarachnoid hemorrhage.
Neurosurg Rev
January 2025
Kobayashi Hospital, 510 Imaichi, Izumo City, Shimane, 693-0001, Japan.
Adverse effects of advanced age and poor initial neurological status on outcomes of patients with aneurysmal subarachnoid hemorrhage (SAH) have been documented. While a predictive model of the non-linear correlation between advanced age and clinical outcome has been reported, no previous model has been validated. Therefore, we created a prediction model of the non-linear correlation between advanced age and clinical outcome by machine learning and validated it using a separate cohort.
View Article and Find Full Text PDFDevelopment and validation of a preoperative nomogram for predicting gallbladder adenoma.
Surg Endosc
January 2025
Department of Hepatopancreatobiliary Surgery, The Second Affiliated Hospital of Kunming Medical University, 374 Dianmian Avenue, Wuhua District, Kunming, 650106, Yunnan, People's Republic of China.
Background: Gallbladder cholesterol polyp (GCP) and gallbladder adenoma (GA) are easily confused in clinical diagnosis. This study aims to establish a nomogram prediction model for preoperative prediction of the risk of GA patients.
Study Design: We retrospectively collected clinical data of GCP or GA patients who underwent laparoscopic cholecystectomy (LC) between January 2020 and April 2023.
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