AIMC Topic: Postoperative Period

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Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.

Scientific reports
Glioblastoma is characterized by diffuse infiltration, making accurate detection of residual disease essential for improving prognostication and guiding treatment. This study evaluates whether the volume of predicted infiltration, generated by a mach...

Multi-channel deep learning radiomics model based on contrast-enhanced CT for predicting postoperative prognosis in laryngeal carcinoma.

BMC cancer
BACKGROUND: Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanc...

Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study.

Scientific reports
Kinesiophobia is particularly common in postoperative lung cancer patients, which causes patients may be reluctant to cough and move due to misperception, internal fear or fear of pain, and avoid rehabilitation training affecting postoperative recove...

Gait Characteristics Associated with Walking Speed in Postoperative Patients with Adult Spinal Deformity Extracted by Machine Learning.

Annals of biomedical engineering
PURPOSE: Patients with adult spinal deformity (ASD) are unable to walk faster even after spinal fixation. Gait rehabilitation that focuses on movements associated with reduced speed may help improve gait function. This study aimed to identify the gai...

Options for postoperative radiation therapy in patients with de novo metastatic breast cancer.

Breast (Edinburgh, Scotland)
BACKGROUND: Although meta-analyses have demonstrated survival benefits associated with primary tumor resection in MBC, guidelines lack consensus on the survival benefit of postoperative radiation therapy (RT).

Video-based multi-target multi-camera tracking for postoperative phase recognition.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning methods are commonly used to generate context understanding to support surgeons and medical professionals. By expanding the current focus beyond the operating room (OR) to postoperative workflows, new forms of assistance are po...

Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models.

Nature communications
Orthognathic surgery, or corrective jaw surgery, is performed to correct severe dentofacial deformities and is increasingly sought for cosmetic purposes. Accurate prediction of surgical outcomes is essential for selecting the optimal treatment plan a...

Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

IEEE journal of biomedical and health informatics
Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone mass andsevere resorption in dental implant therapy. To accurately analyze the geometry changesof the bone graft (BG) in the maxillary sinus (MS), it is...

Prediction of Postoperative Macular Hole Status by Automated Preoperative Retinal OCT Analysis: A Narrative Review.

Ophthalmic surgery, lasers & imaging retina
Optical coherence tomography (OCT) is a non-invasive imaging modality essential for macular hole (MH) management. Artificial intelligence (AI) algorithms could be applied to OCT to garner insights for MH prognosis and outcomes. The objective was to r...

Multicenter study on predicting postoperative upper limb muscle strength improvement in cervical spinal cord injury patients using radiomics and deep learning.

Scientific reports
Cervical spinal cord injury is often catastrophic, frequently leading to irreversible impairment. MRI has become the gold standard for evaluating spinal cord injuries (SCI). Our study aimed to assess the accuracy of a radiomics approach, based on mac...