AIMC Topic: Peritoneal Neoplasms
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A radiomics-based interpretable model integrating delayed-phase CT and clinical features for predicting the pathological grade of appendiceal pseudomyxoma peritonei.
BMC medical imaging
Jul 28, 2025
OBJECTIVE: This study aimed to develop an interpretable machine learning model integrating delayed-phase contrast-enhanced CT radiomics with clinical features for noninvasive prediction of pathological grading in appendiceal pseudomyxoma peritonei (P...
Peritoneal cytology predicting distant metastasis in uterine carcinosarcoma: machine learning model development and validation.
World journal of surgical oncology
Apr 26, 2025
OBJECTIVE: This study develops and validates a machine learning model using peritoneal cytology to predict distant metastasis in uterine carcinosarcoma, aiding clinical decision-making.
A deep-learning model to predict the completeness of cytoreductive surgery in colorectal cancer with peritoneal metastasis☆.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Mar 10, 2025
BACKGROUND: Colorectal cancer (CRC) with peritoneal metastasis (PM) is associated with poor prognosis. The Peritoneal Cancer Index (PCI) is used to evaluate the extent of PM and to select Cytoreductive Surgery (CRS). However, PCI score is not accurat...
Multimodal deep learning: tumor and visceral fat impact on colorectal cancer occult peritoneal metastasis.
European radiology
Feb 17, 2025
OBJECTIVES: This study proposes a multimodal deep learning (DL) approach to investigate the impact of tumors and visceral fat on occult peritoneal metastasis in colorectal cancer (CRC) patients.
Recurrence patterns and prediction of survival after recurrence for gallbladder cancer.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Feb 17, 2025
BACKGROUND: Gallbladder cancer (GBC) is associated with a poor prognosis. Recurrence patterns and their effect on survival remain ill-defined. This study aimed to analyze recurrence patterns and develop a machine learning (ML) model to predict surviv...
Real-Time, AI-Guided Photodynamic Laparoscopy Enhances Detection in a Rabbit Model of Peritoneal Cancer Metastasis.
Cancer science
Feb 10, 2025
Accurate diagnosis is essential for effective cancer treatment, particularly in peritoneal surface malignancies, where failure to detect metastatic lesions can mislead the treatment plan. This study assessed the diagnostic accuracy of staging laparos...
Predicting Postoperative Infection After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy with Splenectomy.
Annals of surgical oncology
Jan 22, 2025
BACKGROUND: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection afte...
Machine learning-based CT radiomics approach for predicting occult peritoneal metastasis in advanced gastric cancer preoperatively.
Clinical radiology
Oct 18, 2024
AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients.
Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Sep 14, 2024
BACKGROUND: Accurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clinic. The collagen alterations in tumor microenvironment affect the migration and treatment response of cancer cells. Herein, we proposed multitask machi...
Comparative assessment of the capability of machine learning-based radiomic models for predicting omental metastasis in locally advanced gastric cancer.
Scientific reports
Jul 13, 2024
The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospect...
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