AIMC Topic: Neoplasm Recurrence, Local
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Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.
The Lancet. Oncology
Jul 5, 2024
BACKGROUND: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We ...
Deep Learning Classification and Quantification of Pejorative and Nonpejorative Architectures in Resected Hepatocellular Carcinoma from Digital Histopathologic Images.
The American journal of pathology
Jun 13, 2024
Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of rec...
Predicting disease recurrence in breast cancer patients using machine learning models with clinical and radiomic characteristics: a retrospective study.
Journal of the Egyptian National Cancer Institute
Jun 10, 2024
BACKGROUND: The goal is to use three different machine learning models to predict the recurrence of breast cancer across a very heterogeneous sample of patients with varying disease kinds and stages.
Prediction of the short-term efficacy and recurrence of photodynamic therapy in the treatment of oral leukoplakia based on deep learning.
Photodiagnosis and photodynamic therapy
Jun 6, 2024
BACKGROUND: The treatment of oral leukoplakia (OLK) with aminolaevulinic acid photodynamic therapy (ALA-PDT) is widespread. Nonetheless, there is variation in efficacy. Therefore, this study constructed a model for predicting the short-term efficacy ...
Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation.
Human genomics
Jun 5, 2024
BACKGROUND: Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15-20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with rec...
Humans
Gene Expression Profiling
Transcriptome
Deep Learning
Liver Neoplasms
Carcinoma, Hepatocellular
Female
Biomarkers, Tumor
Male
Middle Aged
Neoplasm Recurrence, Local
Liver Transplantation
Protein Interaction Maps
Gene Regulatory Networks
Gene Expression Regulation, Neoplastic
Signal Transduction
Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.
Abdominal radiology (New York)
Jun 4, 2024
OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm.
A knowledge-enhanced interpretable network for early recurrence prediction of hepatocellular carcinoma via multi-phase CT imaging.
International journal of medical informatics
Jun 1, 2024
BACKGROUND: Predicting early recurrence (ER) of hepatocellular carcinoma (HCC) accurately can guide treatment decisions and further enhance survival. Computed tomography (CT) imaging, analyzed by deep learning (DL) models combining domain knowledge, ...
Machine learning-based model for predicting tumor recurrence after interventional therapy in HBV-related hepatocellular carcinoma patients with low preoperative platelet-albumin-bilirubin score.
Frontiers in immunology
May 28, 2024
INTRODUCTION: This study aimed to develop a prognostic nomogram for predicting the recurrence-free survival (RFS) of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients with low preoperative platelet-albumin-bilirubin (PALBI) scor...
Prediction of recurrence risk in endometrial cancer with multimodal deep learning.
Nature medicine
May 24, 2024
Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined pathological and molecular profiling is costly, hampering implementation. Here we developed HECTOR (histopa...
Impact of an artificial intelligence based model to predict non-transplantable recurrence among patients with hepatocellular carcinoma.
HPB : the official journal of the International Hepato Pancreato Biliary Association
May 16, 2024
OBJECTIVE: We sought to develop Artificial Intelligence (AI) based models to predict non-transplantable recurrence (NTR) of hepatocellular carcinoma (HCC) following hepatic resection (HR).
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