AIMC Topic: Nomograms
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Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.
Hypertension research : official journal of the Japanese Society of Hypertension
May 9, 2023
In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (...
A novel staging system based on deep learning for overall survival in patients with esophageal squamous cell carcinoma.
Journal of cancer research and clinical oncology
May 8, 2023
PURPOSE: We developed DeepSurv, a deep learning approach for predicting overall survival (OS) in patients with esophageal squamous cell carcinoma (ESCC). We validated and visualized the novel staging system based on DeepSurv using data from multiple ...
Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.
European radiology
May 6, 2023
OBJECTIVES: Using contrast-enhanced computed tomography (CECT) and deep learning technology to develop a deep learning radiomics nomogram (DLRN) to preoperative predict risk status of patients with thymic epithelial tumors (TETs).
Development and validation of novel nomogram to identify the candidates for extended pelvic lymph node dissection for prostate cancer patients in the robotic era.
International journal of urology : official journal of the Japanese Urological Association
May 2, 2023
OBJECTIVES: To determine candidates for extended pelvic lymph node dissection using a novel nomogram to assess the risk of lymph node invasion in Japanese prostate cancer patients in the robotic era.
A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes.
Physical and engineering sciences in medicine
Apr 11, 2023
Continuous glucose monitoring (CGM) data analysis will provide a new perspective to analyze factors related to diabetic retinopathy (DR). However, the problem of visualizing CGM data and automatically predicting the incidence of DR from CGM is still ...
Automated Prediction of Early Recurrence in Advanced Sinonasal Squamous Cell Carcinoma With Deep Learning and Multi-parametric MRI-based Radiomics Nomogram.
Academic radiology
Mar 14, 2023
RATIONALE AND OBJECTIVES: Preoperative prediction of the recurrence risk in patients with advanced sinonasal squamous cell carcinoma (SNSCC) is critical for individualized treatment. To evaluate the predictive ability of radiomics signature (RS) base...
Development and External Validation of a Machine Learning Model for Prediction of Lymph Node Metastasis in Patients with Prostate Cancer.
European urology oncology
Mar 1, 2023
BACKGROUND: Pelvic lymph node dissection (PLND) is the gold standard for diagnosis of lymph node involvement (LNI) in patients with prostate cancer. The Roach formula, Memorial Sloan Kettering Cancer Center (MSKCC) calculator, and Briganti 2012 nomog...
An integrated nomogram combining deep learning, clinical characteristics and ultrasound features for predicting central lymph node metastasis in papillary thyroid cancer: A multicenter study.
Frontiers in endocrinology
Feb 21, 2023
OBJECTIVE: Central lymph node metastasis (CLNM) is a predictor of poor prognosis for papillary thyroid carcinoma (PTC) patients. The options for surgeon operation or follow-up depend on the state of CLNM while accurate prediction is a challenge for r...
Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.
European radiology
Feb 14, 2023
OBJECTIVES: The accurate prediction of post-hepatectomy early recurrence in patients with hepatocellular carcinoma (HCC) is crucial for decision-making regarding postoperative adjuvant treatment and monitoring. We aimed to explore the feasibility of ...
Using deep learning to predict survival outcome in non-surgical cervical cancer patients based on pathological images.
Journal of cancer research and clinical oncology
Jan 19, 2023
PURPOSE: We analyzed clinical features and the representative HE-stained pathologic images to predict 5-year overall survival via the deep-learning approach in cervical cancer patients in order to assist oncologists in designing the optimal treatment...
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