日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Unsupervised clustering analysis reveals distinct postoperative cortisol trajectories following pituitary adenoma resection in Cushing's disease

无监督聚类分析揭示了库欣病患者垂体腺瘤切除术后皮质醇水平的不同变化轨迹。

Khazanchi, Rushmin; Govind, Sachin; Jain, Rishi; Vignolles-Jeong, Joshua; Munjal, Vikas; Chaliparambil, Rahul; Damante, Mark; Chandler, James P; Ghalib, Luma; Huang, Wenyu; Magill, Stephen T; Prevedello, Daniel M

Assessing the ability of large language models to simplify lumbar spine imaging reports into patient-facing text: a pilot study of GPT-4

评估大型语言模型将腰椎影像报告简化为面向患者的文本的能力:GPT-4 的试点研究

Khazanchi, Rushmin; Chen, Austin R; Desai, Parth; Herrera, Daniel; Staub, Jacob R; Follett, Matthew A; Krushelnytskyy, Mykhaylo; Kemeny, Hanna; Hsu, Wellington K; Patel, Alpesh A; Divi, Srikanth N

Identifying high healthcare utilizers following cervical spine surgery using comprehensive predictive modeling techniques

利用综合预测建模技术识别颈椎手术后医疗资源利用率高的患者

Khazanchi, Rushmin; Kumar, Divy; Jain, Rishi; Mittal, Mehul; Bajaj, Anitesh; Oris, Robert J; Chen, Austin R; Joaquin, Theodore A; Herrera, Daniel E; Shah, Rohan M; Asthana, Shravan; Reyes, Samuel G; Bajaj, Pranav; Hsu, Wellington K; Patel, Alpesh A; Divi, Srikanth N

Impact of SGLT2 inhibitors on cerebrospinal fluid dynamics and implications for hydrocephalus management

SGLT2抑制剂对脑脊液动力学的影响及其对脑积水治疗的意义

Sadagopan, Nishanth S; Khazanchi, Rushmin; Jain, Rishi; Heimberger, Amy B; Magill, Stephen T

Assessment of "Zero-Shot" General Purpose Segmentation Models: An Analysis of the Meta "Segment Anything Model" on Meningioma MRI

对“零样本”通用分割模型的评估:基于脑膜瘤MRI的Meta“Segment Anything Model”模型分析

Khazanchi, Rushmin; Govind, Sachin; Congivaram, Harrshavasan T; Sadagopan, Nishanth S; Jain, Rishi; Magill, Stephen T

Predictive Value of Social Determinants of Health on 90-Day Readmission and Health Utilization Following ACDF: A Comparative Analysis of XGBoost, Random Forest, Elastic-Net, SVR, and Deep Learning

社会健康决定因素对颈椎前路椎间盘切除融合术后90天再入院率和医疗资源利用率的预测价值:XGBoost、随机森林、弹性网络、支持向量回归和深度学习的比较分析

Reyes, Samuel G; Bajaj, Pranav M; Herrera, Daniel E; Kurapaty, Steven S; Chen, Austin; Khazanchi, Rushmin; Bajaj, Anitesh; Hsu, Wellington K; Patel, Alpesh A; Divi, Srikanth N

Exploring the Impact of Preoperative Laboratory Values on Short-Term Outcomes in Complex Carpal Tunnel Decompression Surgery

探讨术前实验室检查值对复杂腕管减压手术短期疗效的影响

Bajaj, Anitesh; Khazanchi, Rushmin; Shah, Rohan M; Weissman, Joshua P; Sadagopan, Nishanth S; Gosain, Arun K

Using machine and deep learning to predict short-term complications following trigger digit release surgery

利用机器学习和深度学习预测扳机指松解术后的短期并发症

Shah, Rohan M; Khazanchi, Rushmin; Bajaj, Anitesh; Rana, Krishi; Saklecha, Anjay; Wolf, Jennifer Moriatis

Early Prediction of Poststroke Rehabilitation Outcomes Using Wearable Sensors

利用可穿戴传感器早期预测中风后康复结果

O'Brien, Megan K; Lanotte, Francesco; Khazanchi, Rushmin; Shin, Sung Yul; Lieber, Richard L; Ghaffari, Roozbeh; Rogers, John A; Jayaraman, Arun

Using machine learning to identify risk factors for short-term complications following thumb carpometacarpal arthroplasty

利用机器学习识别拇指腕掌关节成形术后短期并发症的风险因素

Shah, Rohan M; Khazanchi, Rushmin; Bajaj, Anitesh; Rana, Krishi; Malhotra, Saaz; Wolf, Jennifer Moriatis