AI Medical Compendium Journal:
Technology in cancer research & treatment

Showing 1 to 10 of 65 articles

Predicting Mesothelioma Using Artificial Intelligence: A Scoping Review of Common Models and Applications.

Technology in cancer research & treatment
IntroductionMesothelioma is a type of lung cancer caused by asbestos exposure, and early diagnosis is crucial for improving survival chances. Artificial intelligence offers a potential solution for the timely diagnosis and staging of the disease. Thi...

Enhancing Specificity in Predicting Axillary Lymph Node Metastasis in Breast Cancer through an Interpretable Machine Learning Model with CEM and Ultrasound Integration.

Technology in cancer research & treatment
IntroductionThe study aims to evaluate the performance of an interpretable machine learning model in predicting preoperative axillary lymph node metastasis using primary breast cancer and lymph node features derived from contrast-enhanced mammography...

An Ultrasound-based Machine Learning Model for Predicting Tumor-Infiltrating Lymphocytes in Breast Cancer.

Technology in cancer research & treatment
IntroductionTumor-infiltrating lymphocytes (TILs) are key indicators of immune response and prognosis in breast cancer (BC). Accurate prediction of TIL levels is essential for guiding personalized treatment strategies. This study aimed to develop and...

An Early Thyroid Screening Model Based on Transformer and Secondary Transfer Learning for Chest and Thyroid CT Images.

Technology in cancer research & treatment
IntroductionThyroid cancer is a common malignant tumor, and early diagnosis and timely treatment are crucial to improve patient prognosis. With the increasing use of enhanced CT scans, a new opportunity for early thyroid cancer screening has emerged....

Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.

Technology in cancer research & treatment
The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segme...

Focal MRI-Guided Salvage High-Dose-Rate Brachytherapy in Patients With Radiorecurrent Prostate Cancer.

Technology in cancer research & treatment
INTRODUCTION: Whole-gland salvage treatment of radiorecurrent prostate cancer has a high rate of severe toxicity. The standard of care in case of a biochemical recurrence is androgen deprivation treatment, which is associated with morbidity and negat...

PSCA rs1045531 Polymorphism and the Risk of Prostate Cancer in a Chinese Population Undergoing Prostate Biopsy.

Technology in cancer research & treatment
BACKGROUND AND PURPOSE: This study explored the association between a single-nucleotide polymorphism of prostate stem cell antigen and prostate cancer in Chinese patients undergoing prostate biopsy.

Technology advances in hospital practices: robotics in treatment of patients.

Technology in cancer research & treatment
Laparoscopic cholecystectomy is widely considered as the treatment of choice for acute cholecystitis. The safety of the procedure and its minimal invasiveness made it a valid treatment option for a patient not responding to antibiotic therapy. Our re...

Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma.

Technology in cancer research & treatment
Clear cell renal cell carcinoma (ccRCC) is a highly lethal urinary malignancy with poor overall survival (OS) rates. Integrating computer vision and machine learning in pathomics analysis offers potential for enhancing classification, prognosis, and ...

Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier.

Technology in cancer research & treatment
INTRODUCTION: This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patien...