AIMC Topic: Nomograms

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The development of a prediction model based on deep learning for prognosis prediction of gastrointestinal stromal tumor: a SEER-based study.

Scientific reports Mar 19, 2024
Accurately predicting the prognosis of Gastrointestinal stromal tumor (GIST) patients is an important task. The goal of this study was to create and assess models for GIST patients' survival patients using the Surveillance, Epidemiology, and End Resu...
Gastrointestinal Stromal Tumors Calibration Nomograms Area Under Curve SEER Program Humans Prognosis Deep Learning
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Deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram for predicting Ki-67 expression in rectal cancer.

Abdominal radiology (New York) Mar 15, 2024
PURPOSE: To explore the value of deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram in predicting the Ki-67 expression in rectal cancer.
Ki-67 Antigen Multiparametric Magnetic Resonance Imaging Magnetic Resonance Imaging Predictive Value of Tests Rectal Neoplasms Retrospective Studies Female Aged Adult Male Middle Aged Deep Learning Nomograms Humans
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Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

Acta radiologica (Stockholm, Sweden : 1987) Mar 15, 2024
BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate and advanced hepatocellular carcinoma (HCC), with the potential to enhance patient survival. Preoperative prediction of postoperative response to TAC...
Humans Neural Networks, Computer Adult Radiomics Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Female Aged Nomograms Treatment Outcome Chemoembolization, Therapeutic Deep Learning Liver Neoplasms Carcinoma, Hepatocellular
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Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study.

Journal of assisted reproduction and genetics Mar 8, 2024
OBJECTIVE: The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition.
Humans Machine Learning Gene Regulatory Networks Nomograms Endometriosis Phase Separation Biomarkers Retrospective Studies Female Gene Expression Profiling
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Development of a microultrasound-based nomogram to predict extra-prostatic extension in patients with prostate cancer undergoing robot-assisted radical prostatectomy.

Urologic oncology Feb 29, 2024
OBJECTIVES: To develop a microultrasound-based nomogram including clinicopathological parameters and microultrasound findings to predict the presence of extra-prostatic extension and guide the grade of nerve-sparing.
Prostatectomy Nomograms Robotics Prostatic Neoplasms Prostate Humans Retrospective Studies Male
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Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

Journal of computer assisted tomography Feb 27, 2024
OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep lea...
Retrospective Studies Female Aged Adult Humans Prognosis Imaging, Three-Dimensional Nomograms Head and Neck Neoplasms Positron Emission Tomography Computed Tomography Radiomics Male Middle Aged Deep Learning
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Biopsy or Follow-up: AI Improves the Clinical Strategy of US BI-RADS 4A Breast Nodules Using a Convolutional Neural Network.

Clinical breast cancer Feb 20, 2024
OBJECTIVES: To develop predictive nomograms based on clinical and ultrasound features and to improve the clinical strategy for US BI-RADS 4A lesions.
Breast Middle Aged Deep Learning ROC Curve Nomograms Follow-Up Studies Biopsy Ultrasonography, Mammary Female Aged Adult Breast Neoplasms Humans Neural Networks, Computer Retrospective Studies
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A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer.

Biochemical genetics Feb 14, 2024
Comprehensive action patterns of programmed cell death (PCD) in bladder cancer (BLCA) have not yet been thoroughly investigated. Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed a multiple programmed cell ...
Nomograms Urinary Bladder Neoplasms Apoptosis Humans Machine Learning Prognosis Female Male Computational Biology
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Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.

Oral surgery, oral medicine, oral pathology and oral radiology Feb 3, 2024
OBJECTIVE: This study aimed to establish a combined method of radiomics and deep learning (DL) in magnetic resonance imaging (MRI) to predict lymph node metastasis (LNM) preoperatively in patients with squamous cell carcinoma of the tongue.
Humans Retrospective Studies Female Carcinoma, Squamous Cell Aged Adult Predictive Value of Tests Tongue Neoplasms Deep Learning Nomograms Lymphatic Metastasis Magnetic Resonance Imaging Radiomics Male Middle Aged
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Robot-assisted versus laparoscopic pheochromocytoma resection and construction of a nomogram to predict perioperative hemodynamic instability.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Feb 1, 2024
BACKGROUND: Despite recent improvements in perioperative outcomes after pheochromocytoma resection, hemodynamic instability (HI) remained of high concern. The emergence of robot-assisted surgery may bring different results to pheochromocytoma surgery...
Adrenal Gland Neoplasms Robotics Laparoscopy Pheochromocytoma Humans Retrospective Studies Hemodynamics Nomograms
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