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Precision Health Database


Genomics & Health Impact Scan Database|Search|PHGKB

Last data update: Aug 18, 2022. (Total: 48929 Documents since 2012)
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Using machine learning for mortality prediction and risk stratification in atezolizumab-treated cancer patients: Integrative analysis of eight clinical trials.
Wu Yougen et al. Cancer medicine 2022
A novel analytical framework for risk stratification of real-world data using machine learning: a small cell lung cancer (SCLC) study.
Marzano Luca et al. Clinical and translational science 2022
Deep Learning Empowers Lung Cancer Screening Based on Mobile Low-Dose Computed Tomography in Resource-Constrained Sites.
Shao Jun et al. Frontiers in bioscience (Landmark edition) 2022 27(7) 212
A narrative review of deep learning applications in lung cancer research: from screening to prognostication.
Lee Jong Hyuk et al. Translational lung cancer research 2022 11(6) 1217-1229
Risk factors and prognostic nomogram for patients with second primary cancers after lung cancer using classical statistics and machine learning.
Luo Lianxiang et al. Clinical and experimental medicine 2022
Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis.
Pei Qin et al. Clinical chemistry and laboratory medicine 2022
Semi-supervised approach to event time annotation using longitudinal electronic health records.
Liang Liang et al. Lifetime data analysis 2022
Use of deep learning to predict postoperative recurrence of lung adenocarcinoma from preoperative CT.
Sasaki Yuki et al. International journal of computer assisted radiology and surgery 2022
Machine learning-based gene alteration prediction model for primary lung cancer using cytologic images.
Ishii Shuhei et al. Cancer cytopathology 2022
Prognostic impact of artificial intelligence-based volumetric quantification of the solid part of the tumor in clinical stage 0-I adenocarcinoma.
Kawaguchi Yohei et al. Lung cancer (Amsterdam, Netherlands) 2022 17085-90
Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest.
Naseri Hossein et al. Scientific reports 2022 12(1) 9866
Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations.
Lee Jong Hyuk et al. Radiology 2022 212877
The application of artificial intelligence and radiomics in lung cancer.
Zhou Yaojie et al. Precision clinical medicine 2022 3(3) 214-227
Machine Learning for the Prediction of Synchronous Organ-Specific Metastasis in Patients With Lung Cancer.
Gao Huan et al. Frontiers in oncology 2022 12817372
Improving the Accuracy of Ensemble Machine Learning Classification Models Using a Novel Bit-Fusion Algorithm for Healthcare AI Systems.
Mishra Sashikala et al. Frontiers in public health 2022 10858282
Development of Diagnosis Model for Early Lung Nodules Based on a Seven Autoantibodies Panel and Imaging Features.
Xu Leidi et al. Frontiers in oncology 2022 12883543
Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population.
Murchison John T et al. PloS one 2022 17(5) e0266799
Machine learning application in personalised lung cancer recurrence and survivability prediction.
Yang Yang et al. Computational and structural biotechnology journal 2022 201811-1820
Using Natural Language Processing and Machine Learning to Preoperatively Predict Lymph Node Metastasis for Non-Small Cell Lung Cancer With Electronic Medical Records: Development and Validation Study.
Hu Danqing et al. JMIR medical informatics 2022 10(4) e35475
Deep Learning-based Artificial Intelligence Improves Accuracy of Error-prone Lung Nodules.
Lan Chou-Chin et al. International journal of medical sciences 2022 19(3) 490-498
The Value of Artificial Intelligence Film Reading System Based on Deep Learning in the Diagnosis of Non-Small-Cell Lung Cancer and the Significance of Efficacy Monitoring: A Retrospective, Clinical, Nonrandomized, Controlled Study.
Chen Yunbing et al. Computational and mathematical methods in medicine 2022 20222864170
Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.
Yuan Luo et al. Journal of X-ray science and technology 2022
On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer.
Mohamed Sameh K et al. AMIA ... Annual Symposium proceedings. AMIA Symposium 2022 2021853-862
A Classifier for Improving Early Lung Cancer Diagnosis Incorporating Artificial Intelligence and Liquid Biopsy.
Ye Maosong et al. Frontiers in oncology 2022 12853801
Optimizing the radiomics-machine-learning model based on non-contrast enhanced CT for the simplified risk categorization of thymic epithelial tumors: A large cohort retrospective study.
Feng Xiu-Long et al. Lung cancer (Amsterdam, Netherlands) 2022 166150-160
A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models.
Hindocha Sumeet et al. EBioMedicine 2022 77103911
On the Automation of Radiomics-based Identification and Characterization of NSCLC.
D'Arnese Eleonora et al. IEEE journal of biomedical and health informatics 2022 PP
Analysis of the Diagnosis Model of Peripheral Non-Small-Cell Lung Cancer under Computed Tomography Images.
Xie Zhonghai et al. Journal of healthcare engineering 2022 20223107965
Augmented Features Synergize Radiomics in Post-Operative Survival Prediction and Adjuvant Therapy Recommendation for Non-Small Cell Lung Cancer.
Chan Lawrence Wing-Chi et al. Frontiers in oncology 2022 12659096
Computer-aided detection of pulmonary nodules based on convolutional neural networks: a review.
Min Yuqin et al. Physics in medicine and biology 2022
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