AIMC Topic: Neoplasm Recurrence, Local

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Impact of the number of dissected lymph nodes on machine learning-based prediction of postoperative lung cancer recurrence: a single-hospital retrospective cohort study.

BMJ open respiratory research Sep 26, 2024
BACKGROUND: The optimal number of lymph nodes to be dissected during lung cancer surgery to minimise the postoperative recurrence risk remains undetermined. This study aimed to elucidate the impact of the number of dissected lymph nodes on the risk o...
Middle Aged Lung Neoplasms Lymph Nodes Carcinoma, Non-Small-Cell Lung Lymphatic Metastasis Lymph Node Excision Pneumonectomy Neoplasm Recurrence, Local Machine Learning Retrospective Studies Female Aged Male Humans
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Upfront surgery for intrahepatic cholangiocarcinoma: Prediction of futility using artificial intelligence.

Surgery Sep 24, 2024
OBJECTIVE: We sought to identify patients at risk of "futile" surgery for intrahepatic cholangiocarcinoma using an artificial intelligence (AI)-based model based on preoperative variables.
Middle Aged Risk Assessment Deep Learning ROC Curve Neoplasm Recurrence, Local Retrospective Studies Female Aged Male Hepatectomy Bile Duct Neoplasms Cholangiocarcinoma Medical Futility Humans Artificial Intelligence
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A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET-Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study.

JMIR cancer Sep 20, 2024
BACKGROUND: Salvage radiation therapy (sRT) is often the sole curative option in patients with biochemical recurrence after radical prostatectomy. After sRT, we developed and validated a nomogram to predict freedom from biochemical failure.
Machine Learning Retrospective Studies Aged Male Middle Aged Humans Radiotherapy, Image-Guided Positron-Emission Tomography Salvage Therapy Prostatectomy Antigens, Surface Nomograms Glutamate Carboxypeptidase II Prostatic Neoplasms Prostate-Specific Antigen Neoplasm Recurrence, Local
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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...
Collagen Chemotherapy, Adjuvant Humans Middle Aged Machine Learning Neoplasm Recurrence, Local Prognosis Peritoneal Neoplasms Female Disease-Free Survival Aged Stomach Neoplasms Survival Rate Tumor Microenvironment Male
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An artificial intelligence-based model exploiting H&E images to predict recurrence in negative sentinel lymph-node melanoma patients.

Journal of translational medicine Sep 12, 2024
BACKGROUND: Risk stratification and treatment benefit prediction models are urgent to improve negative sentinel lymph node (SLN-) melanoma patient selection, thus avoiding costly and toxic treatments in patients at low risk of recurrence. To this end...
Humans Artificial Intelligence Female Middle Aged ROC Curve Neoplasm Recurrence, Local Sentinel Lymph Node Recurrence Melanoma Reproducibility of Results Aged Adult Male
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Prognostic model for predicting recurrence in hepatocellular carcinoma patients with high systemic immune-inflammation index based on machine learning in a multicenter study.

Frontiers in immunology Sep 9, 2024
INTRODUCTION: This study aims to use machine learning to conduct in-depth analysis of key factors affecting the recurrence of HCC patients with high preoperative systemic immune-inflammation index (SII) levels after receiving ablation treatment, and ...
Liver Neoplasms Carcinoma, Hepatocellular Inflammation Nomograms Neoplasm Recurrence, Local Humans Machine Learning Risk Factors Prognosis Aged Female Adult Male Middle Aged
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Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Journal of vascular and interventional radiology : JVIR Aug 28, 2024
PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical ...
Aged Radiomics Male Middle Aged Risk Assessment Tomography, X-Ray Computed Humans Clinical Decision-Making Machine Learning Female Radiographic Image Interpretation, Computer-Assisted Time Factors Decision Support Techniques Risk Factors Neoplasm Recurrence, Local Lung Neoplasms Retrospective Studies Microwaves Treatment Outcome Margins of Excision Predictive Value of Tests Adenocarcinoma of Lung Neoplasm Staging Ablation Techniques
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Use of Natural Language Processing to Extract and Classify Papillary Thyroid Cancer Features From Surgical Pathology Reports.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists Aug 26, 2024
BACKGROUND: We aim to use Natural Language Processing to automate the extraction and classification of thyroid cancer risk factors from pathology reports.
Thyroid Neoplasms Natural Language Processing Neoplasm Recurrence, Local Humans Thyroid Cancer, Papillary Risk Factors Pathology, Surgical Adult
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Development of an artificial intelligence-based model to predict early recurrence of neuroendocrine liver metastasis after resection.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract Aug 26, 2024
PURPOSE: We sought to develop an artificial intelligence (AI)-based model to predict early recurrence (ER) after curative-intent resection of neuroendocrine liver metastases (NELMs).
Humans Artificial Intelligence Prognosis Retrospective Studies Female Aged Adult Hepatectomy Male Neuroendocrine Tumors Middle Aged Liver Neoplasms ROC Curve Predictive Value of Tests Neoplasm Recurrence, Local Tumor Burden
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Artificial intelligence-based model for the recurrence of hepatocellular carcinoma after liver transplantation.

Surgery Aug 23, 2024
BACKGROUND: Artificial intelligence-based models might improve patient selection for liver transplantation in hepatocellular carcinoma. The objective of the current study was to develop artificial intelligence-based deep learning models and determine...
Liver Transplantation Patient Selection Disease-Free Survival Female Adult Male Middle Aged Risk Assessment Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Living Donors Humans Neoplasm Recurrence, Local Artificial Intelligence Retrospective Studies
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