Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

Precision Health Database


Precision Health Database|Search|PHGKB

Cancer

Last data update: Dec 08, 2023. (Total: 62298 Documents since 2012)
   dataset      
Filtered By:

Previous    

Records 1 - 30 (of 2133 Records)

Next

Query Trace: all[original query]
Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance.
Lucy Thomas et al. Front Med (Lausanne) 2023 101264846
Analysis of computational intelligence approaches for predicting disease severity in humans: Challenges and research guidelines.
Geetha Narasimhan et al. J Educ Health Promot 2023 12334
TransformEHR: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records.
Zhichao Yang et al. Nat Commun 2023 14(1) 7857
Deep-learning-based survival prediction of patients with lower limb melanoma.
Jinrong Zhang et al. Discov Oncol 2023 14(1) 218
Transforming cancer clinical trials: The integral role of artificial intelligence in electronic health records for efficient patient recruitment.
Abdulqadir J Nashwan et al. Contemp Clin Trials Commun 2023 36101223
Clinico-biological-radiomics (CBR) based machine learning for improving the diagnostic accuracy of FDG-PET false-positive lymph nodes in lung cancer.
Caiyue Ren et al. Eur J Med Res 2023 28(1) 554
Artificial Intelligence for the Management of Breast Cancer: An Overview.
Kapil Kumar et al. Curr Drug Discov Technol 2023
Machine learning improves prediction of clinical outcomes for invasive breast cancers.
et al. Nat Med 2023
A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer.
Mohamed Amgad et al. Nat Med 2023
Large-scale pancreatic cancer detection via non-contrast CT and deep learning.
Kai Cao et al. Nat Med 2023
Comparing Active Surveillance and Watchful Waiting With Radical Treatment Using Machine Learning Models Among Patients With Prostate Cancer.
Siqi Hu et al. JCO Clin Cancer Inform 2023 7e2300083
Application of CT and MRI images based on an artificial intelligence algorithm for predicting lymph node metastasis in breast cancer patients: a meta-analysis.
Cheng-Jie Liu et al. BMC Cancer 2023 23(1) 1134
Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.
Hee Sang Oh et al. Eur Radiol 2023
Impact of real-life use of artificial intelligence as support for human reading in a population-based breast cancer screening program with mammography and tomosynthesis.
Esperanza Elías-Cabot et al. Eur Radiol 2023
Artificial Intelligence in Melanoma Dermatopathology: A Review of Literature.
Hannah Neimy et al. Am J Dermatopathol 2023
Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development.
Malin Hjärtström et al. JMIR Cancer 2023 9e46474
Population-wide evaluation of artificial intelligence and radiologist assessment of screening mammograms.
Johanne Kühl et al. Eur Radiol 2023
Skin cancer diagnosis (SCD) using Artificial Neural Network (ANN) and Improved Gray Wolf Optimization (IGWO).
Wanqi Lai et al. Sci Rep 2023 13(1) 19377
Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy.
Rong-Rong Wu et al. Sci Rep 2023 13(1) 19409
From cancer big data to treatment: Artificial intelligence in cancer research.
Danishuddin et al. J Gene Med 2023 e3629
Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review.
Cody M Schopf et al. J Am Coll Radiol 2023
ML-DSTnet: A Novel Hybrid Model for Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning and Dempster-Shafer Theory.
Mohsen Eftekharian et al. Comput Intell Neurosci 2023 20237510419
Evaluation of a Natural Language Processing Model to Identify and Characterize Patients in the United States With High-Risk Non-Muscle-Invasive Bladder Cancer.
Vikram M Narayan et al. JCO Clin Cancer Inform 2023 7e2300096
A machine learning-based prediction model of pelvic lymph node metastasis in women with early-stage cervical cancer.
Kamonrat Monthatip et al. J Gynecol Oncol 2023
Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.
Hao Zhong et al. Ann Surg Oncol 2023
Predicting diagnosis and survival of bone metastasis in breast cancer using machine learning.
Xugang Zhong et al. Sci Rep 2023 13(1) 18301
Development and validation of an artificial intelligence prediction model and a survival risk stratification for lung metastasis in colorectal cancer from highly imbalanced data: A multicenter retrospective study.
Weiyuan Zhang et al. Eur J Surg Oncol 2023 49(12) 107107
Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans.
Ward Hendrix et al. Commun Med (Lond) 2023 3(1) 156
Development of machine learning prognostic models for overall survival of prostate cancer patients with lymph node-positive.
Zi-He Peng et al. Sci Rep 2023 13(1) 18424
The Role of Artificial Intelligence in Prospective Real-Time Histological Prediction of Colorectal Lesions during Colonoscopy: A Systematic Review and Meta-Analysis.
Bhamini Vadhwana et al. Diagnostics (Basel) 2023 13(20)
TOP