About Non-Genomics Precision Health Scan
This update features emerging roles of big data science, machine learning, and predictive analytics across the life span. The scan focus on various conditions including, birth defects, newborn screening, reproductive health, childhood diseases, cancer, chronic diseases, medication, family health history, guidelines and recommendations. The sweep also includes news, reviews, commentaries, tools and database. View Data Selection Criteria
Non-Genomics Precision Health Scan
The Prediction of Preterm Birth Using Time-Series Technology-Based Machine Learning: Retrospective Cohort Study.
Zhang Yichao et al. JMIR medical informatics 2022 10(6) e33835
Extraction of Treatment Information From Electronic Health Records and Evaluation of Testosterone Recovery in Patients With Prostate Cancer.
Guin Sunny et al. JCO clinical cancer informatics 2022 6e2200010
The application of artificial intelligence and radiomics in lung cancer.
Zhou Yaojie et al. Precision clinical medicine 2022 3(3) 214-227
Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images.
Zhao Ke et al. Precision clinical medicine 2022 4(1) 17-24
Predicting biochemical recurrence of prostate cancer with artificial intelligence.
Pinckaers Hans et al. Communications medicine 2022 264
A machine-learning algorithm for distinguishing malignant from benign indeterminate thyroid nodules using ultrasound radiomic features.
Keutgen Xavier M et al. Journal of medical imaging (Bellingham, Wash.) 2022 9(3) 034501
Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations.
Lee Jong Hyuk et al. Radiology 2022 212877
Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning.
Vasanthakumari Priyanka et al. Journal of biomedical optics 2022 27(6)
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
A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation.
Stafford Imogen S et al. Inflammatory bowel diseases 2022
An Artificial-Intelligence-Based Automated Grading and Lesions Segmentation System for Myopic Maculopathy Based on Color Fundus Photographs.
Tang Jia et al. Translational vision science & technology 2022 11(6) 16
The promise of artificial intelligence for kidney pathophysiology.
Jiang Joy et al. Current opinion in nephrology and hypertension 2022
Predicting the future of neuroimaging predictive models in mental health.
Tejavibulya Link et al. Molecular psychiatry 2022
A Primer into the Current State of Artificial Intelligence in Gastroenterology.
Moldoveanu Alexandru Constantin et al. Journal of gastrointestinal and liver diseases : JGLD 2022 31(2) 244-253
The Contribution of Chest X-Ray to Predict Extubation Failure in Mechanically Ventilated Patients Using Machine Learning-Based Algorithms.
Fukuchi Kiyoyasu et al. Critical care explorations 2022 4(6) e0718
Perspective of Information Technology Decision Makers on Factors Influencing Adoption and Implementation of Artificial Intelligence Technologies in 40 German Hospitals: Descriptive Analysis.
Weinert Lina et al. JMIR medical informatics 2022 10(6) e34678
Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study.
Yacoub Basel et al. AJR. American journal of roentgenology 2022
Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-resolution Computed Tomography.
Walsh Simon Lf et al. American journal of respiratory and critical care medicine 2022
Artificial intelligence and imaging: Opportunities in cardio-oncology.
Madan Nidhi et al. American heart journal plus : cardiology research and practice 2022 15
Machine-learning Algorithms for Ischemic Heart Disease Prediction: A systematic Review.
Bani Hani Salam H et al. Current cardiology reviews 2022
Validation of Artificial Intelligence Cardiac MRI Measurements: Relationship to Heart Catheterization and Mortality Prediction.
Alabed Samer et al. Radiology 2022 212929
Classification of multi-lead ECG with deep residual convolutional neural networks.
Cai Wenjie et al. Physiological measurement 2022
Deep learning models for forecasting dengue fever based on climate data in Vietnam.
Hau Nguyen Van et al. PLoS neglected tropical diseases 2022 16(6) e0010509
Prediction of Prognostic Risk Factors in Patients with Invasive Candidiasis and Cancer: A Single-Centre Retrospective Study.
Li Jingyi et al. BioMed research international 2022 20227896218
Effect of smartphone app-based health care intervention for health management of high-risk mothers: a study protocol for a randomized controlled trial.
Kim Bora et al. Trials 2022 23(1) 486
Disclaimer: Articles listed in Non-Genomics Precision Health Scan are selected by the CDC Office of Genomics and Precision Public Health to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
- Page last reviewed:Feb 1, 2024
- Page last updated:Apr 15, 2024
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