AIMC Topic: Neoplasm Staging
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Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients.
Lung cancer (Amsterdam, Netherlands)
Jan 4, 2025
BACKGROUND: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with ad...
Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.
Lung cancer (Amsterdam, Netherlands)
Jan 2, 2025
OBJECTIVES: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through...
Gene Expression Regulation, Neoplastic
Antineoplastic Combined Chemotherapy Protocols
Treatment Outcome
Neoplasm Staging
Gene Expression Profiling
Transcriptome
Lung Neoplasms
Immunotherapy
Machine Learning
Small Cell Lung Carcinoma
Prospective Studies
Aged
Humans
Prognosis
Biomarkers, Tumor
Male
Female
Middle Aged
Multi-Modal Federated Learning for Cancer Staging Over Non-IID Datasets With Unbalanced Modalities.
IEEE transactions on medical imaging
Jan 2, 2025
The use of machine learning (ML) for cancer staging through medical image analysis has gained substantial interest across medical disciplines. When accompanied by the innovative federated learning (FL) framework, ML techniques can further overcome pr...
Machine Learning Prediction of Early Recurrence in Gastric Cancer: A Nationwide Real-World Study.
Annals of surgical oncology
Dec 30, 2024
BACKGROUND: Patients with gastric cancer (GC) who experience early recurrence (ER) within 2 years postoperatively have poor prognoses. This study aimed to analyze and predict ER after curative surgery for patients with GC using machine learning (ML) ...
Multimodal Deep Learning Fusing Clinical and Radiomics Scores for Prediction of Early-Stage Lung Adenocarcinoma Lymph Node Metastasis.
Academic radiology
Dec 27, 2024
RATIONALE AND OBJECTIVES: To develop and validate a multimodal deep learning (DL) model based on computed tomography (CT) images and clinical knowledge to predict lymph node metastasis (LNM) in early lung adenocarcinoma.
Machine learning in personalized laryngeal cancer management: insights into clinical characteristics, therapeutic options, and survival predictions.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Dec 23, 2024
PURPOSE: Over the last 40 years, there has been an unusual trend where, even though there are more varied treatments, survival rates have not improved much. Our study used survival analysis and machine learning (ML) to investigate this odd situation ...
Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought: Algorithm Development and Validation Study.
JMIR medical informatics
Dec 20, 2024
BACKGROUND: Traditional rule-based natural language processing approaches in electronic health record systems are effective but are often time-consuming and prone to errors when handling unstructured data. This is primarily due to the substantial man...
Combined inflammation-related biomarkers and clinicopathological features for the prognosis of stage II/III colorectal cancer by machine learning.
BMC cancer
Dec 18, 2024
BACKGROUND: Inflammation-related biomarkers, such as systemic inflammation score (SIS) and neutrophil-lymphocyte ratio (NLR), are associated with colorectal cancer prognosis. However, the combined role of SIS, NLR, and clinicopathological factors in ...
Uncertainty-aware automatic TNM staging classification for [F] Fluorodeoxyglucose PET-CT reports for lung cancer utilising transformer-based language models and multi-task learning.
BMC medical informatics and decision making
Dec 18, 2024
BACKGROUND: [F] Fluorodeoxyglucose (FDG) PET-CT is a clinical imaging modality widely used in diagnosing and staging lung cancer. The clinical findings of PET-CT studies are contained within free text reports, which can currently only be categorised ...
Artificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.
International journal of gynecological cancer : official journal of the International Gynecological Cancer Society
Dec 17, 2024
OBJECTIVE: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optimal treatment planning and prognosis assessment. This study proposes a deep learning pipeline for tumor and uterus segmentation from magnetic resonance...
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