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A Multimodal Cross-View Model for Predicting Postoperative Neck Pain in Cervical Spondylosis Patients

2025-09-02 · Jingyang Shan, Qishuai Yu, Jiacen Liu, Shaolin Zhang, Wen Shen, Yanxiao Zhao, Tianyi Wang, Xiaolin Qin, Yiheng Yin arxiv

Neck pain is the primary symptom of cervical spondylosis, yet its underlying mechanisms remain unclear, leading to uncertain treatment outcomes. To address the challenges of multimodal feature fusion caused by imaging differences and spatial mismatches, this paper proposes an Adaptive Bidirectional Pyramid Difference Convolution (ABPDC) module that facilitates multimodal integration by exploiting the advantages of difference convolution in texture extraction and grayscale invariance, and a Feature Pyramid Registration Auxiliary Network (FPRAN) to mitigate structural misalignment. Experiments on the MMCSD dataset demonstrate that the proposed model achieves superior prediction accuracy of postoperative neck pain recovery compared with existing methods, and ablation studies further confirm its effectiveness.

📄 PDF Abstract BibTeX arXiv:2509.02256

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CTT-Net: A Multi-view Cross-token Transformer for Cataract Postoperative Visual Acuity Prediction

2022-12-12 · Jinhong Wang, Jingwen Wang, Tingting Chen, Wenhao Zheng 외

Surgery is the only viable treatment for cataract patients with visual acuity (VA) impairment. Clinically, to assess the necessity of cataract surgery, accurately predicting postoperative VA before surgery by analyzing m…

regression

A Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients

2024-12-02 · Junbo Shen, Bing Xue, Thomas Kannampallil, Chenyang Lu 외

Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We develope…

Prognosis Representation Learning

Prediction of Post-Operative Renal and Pulmonary Complications Using Transformers

2023-06-01 · Reza Shirkavand, Fei Zhang, Heng Huang

Postoperative complications pose a significant challenge in the healthcare industry, resulting in elevated healthcare expenses and prolonged hospital stays, and in rare instances, patient mortality. To improve patient ou…

Deep Learning Management

Dynamic Predictions of Postoperative Complications from Explainable, Uncertainty-Aware, and Multi-Task Deep Neural Networks

2020-04-27 · Benjamin Shickel, Tyler J. Loftus, Matthew Ruppert, Gilbert R. Upchurch 외

Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, preoperative risk-reduction, and postoperative resource use. We hypothesized that multi-task deep learning models would …

Decision Making Deep Learning Multi-Task Learning Prognosis+2

Multimodal Spatio-Temporal Deep Learning Approach for Neonatal Postoperative Pain Assessment

2020-12-03 · Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi 외

The current practice for assessing neonatal postoperative pain relies on bedside caregivers. This practice is subjective, inconsistent, slow, and discontinuous. To develop a reliable medical interpretation, several autom…