Fluorodeoxyglucose F18

A machine learning-based 18F-FDG PET/CT multi-modality fusion radiomics model to predict Mediastinal-Hilar lymph node metastasis in NSCLC: a multi-centre study.

Clinical radiology 39983386

AIM: To develop and validate a machine learning (ML) model based on positron emission tomography/computed tomography (PET/CT) multi-modality fusion radiomics to improve the prediction efficiency of mediastinal-hilar lymph node metastasis (LNM).

Adult Aged Carcinoma, Non-Small-Cell Lung Female Fluorodeoxyglucose F18 Humans Lung Neoplasms Lymph Nodes Lymphatic Metastasis Machine Learning Male Mediastinum Middle Aged Positron Emission Tomography Computed Tomography Radiomics Radiopharmaceuticals Retrospective Studies

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F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients.

La Radiologia medica 39875749

PURPOSE: Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients based on conventional and radiomic signatures extracted from baseline [F]FDG PET/CT.

Adult Aged Artificial Intelligence Breast Neoplasms Chemotherapy, Adjuvant Female Fluorodeoxyglucose F18 Humans Lymphatic Metastasis Machine Learning Middle Aged Neoadjuvant Therapy Positron Emission Tomography Computed Tomography Predictive Value of Tests Radiomics Radiopharmaceuticals Retrospective Studies Treatment Outcome

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F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

Asian Pacific journal of cancer prevention : APJCP 39873989

OBJECTIVE: This study aimed to develop a simple machine-learning model incorporating lymph node metastasis status with F-18 Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) and clinical information for predicting regio...

Adult Aged Aged, 80 and over Colonic Neoplasms Female Fluorodeoxyglucose F18 Follow-Up Studies Humans Lymph Nodes Lymphatic Metastasis Machine Learning Male Middle Aged Positron Emission Tomography Computed Tomography Prognosis Radiopharmaceuticals Retrospective Studies ROC Curve

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Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

Journal of cancer research and clinical oncology 39976736

PURPOSE: The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients...

Adult Aged Algorithms Artificial Intelligence Female Fluorodeoxyglucose F18 Humans Machine Learning Middle Aged Neoplasm Staging Ovarian Neoplasms Positron Emission Tomography Computed Tomography Radiomics Radiopharmaceuticals Retrospective Studies

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Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

Cancer imaging : the official publication of the International Cancer Imaging Society 39966960

BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for precise treatment planning. This study aims to utilize convolutional neural networks based on dual-time-point F-FDG PET/CT to predict the malignant ris...

Adult Aged Convolutional Neural Networks Female Fluorodeoxyglucose F18 Humans Lung Neoplasms Male Middle Aged Neural Networks, Computer Positron Emission Tomography Computed Tomography Radiopharmaceuticals Retrospective Studies Solitary Pulmonary Nodule

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Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning.

BMC medical imaging 39962481

BACKGROUND: 18-Fluoro-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is a valuable imaging tool widely used in the management of cancer patients. Deep learning models excel at segmenting highly metabolic tumors but face ch...

Aged Deep Learning Female Fluorodeoxyglucose F18 Humans Intestinal Neoplasms Male Middle Aged Positron Emission Tomography Computed Tomography Radiopharmaceuticals Whole Body Imaging

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Reducing inference cost of Alzheimer's disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners.

Scientific reports 39952976

While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG PET) data have shown promise in the accurate identification of Alzheimer's disease, their clinical appl...

Alzheimer Disease Brain Deep Learning Fluorodeoxyglucose F18 Humans Magnetic Resonance Imaging Positron-Emission Tomography Uncertainty

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Impact of [F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role.

Seminars in nuclear medicine 40050131

Lung cancer remains one of the most prevalent cancers globally and the leading cause of cancer-related deaths, accounting for nearly one-fifth of all cancer fatalities. Fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ([F]FDG...

Artificial Intelligence Clinical Decision-Making Fluorodeoxyglucose F18 Humans Image Processing, Computer-Assisted Lung Neoplasms Positron Emission Tomography Computed Tomography Radiomics

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Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non-Small Cell Lung Cancer.

JCO clinical cancer informatics 40043221

PURPOSE: To comprehensively analyze the association between preoperative maximum standardized uptake value (SUV) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography and postoperative recurrence in resected non-small cell lung c...

Aged Carcinoma, Non-Small-Cell Lung Female Fluorodeoxyglucose F18 Humans Lung Neoplasms Machine Learning Male Middle Aged Neoplasm Recurrence, Local Positron Emission Tomography Computed Tomography Preoperative Period Prognosis Retrospective Studies ROC Curve

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The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine 40081959

This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep learning (DL) in [F]FDG and [Ga]Ga-prostate-specific membrane antigen (PSMA) PET/CT scans. We used 489 ...

Aged Automation Deep Learning Edetic Acid Fluorodeoxyglucose F18 Gallium Isotopes Gallium Radioisotopes Humans Image Processing, Computer-Assisted Male Middle Aged Oligopeptides Positron Emission Tomography Computed Tomography

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Explore the latest research on artificial intelligence and machine learning in medicine.

A machine learning-based 18F-FDG PET/CT multi-modality fusion radiomics model to predict Mediastinal-Hilar lymph node metastasis in NSCLC: a multi-centre study.

F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients.

F-18 FDG PET/CT based Preoperative Machine Learning Prediction Models for Evaluating Regional Lymph Node Metastasis Status of Patients with Colon Cancer.

Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning.

Reducing inference cost of Alzheimer's disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners.

Impact of [F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role.

Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non-Small Cell Lung Cancer.

The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

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