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
Machine Learning Model Based on the Neutrophil-to-Eosinophil Ratio Predicts the Recurrence of Hepatocellular Carcinoma After Surgery.
Guanming Shao et al. J Hepatocell Carcinoma 2024 11679-691
Is Risk-Stratifying Patients with Colorectal Cancer Using a Deep Learning-Based Prognostic Biomarker Cost-Effective?
Anna Kenseth et al. Pharmacoeconomics 2024
Evaluation of the neoadjuvant chemotherapy response in osteosarcoma using the MRI DWI-based machine learning radiomics nomogram.
Lu Zhang et al. Front Oncol 2024 141345576
Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.
Sena Alaeikhanehshir et al. Cancer Imaging 2024 24(1) 48
Incremental value of automatically segmented perirenal adipose tissue for pathological grading of clear cell renal cell carcinoma: a multicenter cohort study.
Shichao Li et al. Int J Surg 2024
Artificial intelligence and skin cancer.
Maria L Wei et al. Front Med (Lausanne) 2024 111331895
Predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma using deep learning.
Yu Wang et al. PeerJ 2024 12e16952
Radiomics-based prediction of nonalcoholic fatty liver disease following pancreatoduodenectomy.
Takehiro Fujii et al. Surg Today 2024
Development and validation of a machine learning model for prediction of type 2 diabetes in patients with mental illness.
Martin Bernstorff et al. Acta Psychiatr Scand 2024
Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer's disease detection.
Viswan Vimbi et al. Brain Inform 2024 11(1) 10
Machine Learning for prediction of violent behaviors in schizophrenia spectrum disorders: a systematic review.
Mohammadamin Parsaei et al. Front Psychiatry 2024 151384828
Performance Evaluation of Deep, Shallow and Ensemble Machine Learning Methods for the Automated Classification of Alzheimer's Disease.
Noushath Shaffi et al. Int J Neural Syst 2024 2450029
Algor-ethics: charting the ethical path for AI in critical care.
Jonathan Montomoli et al. J Clin Monit Comput 2024
Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study.
Andrew J McMurry et al. J Med Internet Res 2024 26e53367
Identifying Psychosis Episodes in Psychiatric Admission Notes via Rule-based Methods, Machine Learning, and Pre-Trained Language Models.
Yining Hua et al. Res Sq 2024
Identifying Psychosis Episodes in Psychiatric Admission Notes via Rule-based Methods, Machine Learning, and Pre-Trained Language Models.
Yining Hua et al. medRxiv 2024
Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review protocol.
Joana Seringa et al. BMJ Open 2024 14(4) e083188
Machine learning-based predictive models for patients with venous thromboembolism: A Systematic Review.
Vasiliki Danilatou et al. Thromb Haemost 2024
Machine Learning-Based Prediction of Stroke in Emergency Departments.
Vida Abedi et al. Ther Adv Neurol Disord 2024 1717562864241239108
Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.
Faraz S Ahmad et al. Clin Res Cardiol 2024
Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing.
Marta Fernandes et al. medRxiv 2024
Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound.
Evangelos K Oikonomou et al. medRxiv 2024
Comprehensive evaluation and performance analysis of machine learning in heart disease prediction.
Halah A Al-Alshaikh et al. Sci Rep 2024 14(1) 7819
A comprehensive review on efficient artificial intelligence models for classification of abnormal cardiac rhythms using electrocardiograms.
Utkarsh Gupta et al. Heliyon 2024 10(5) e26787
Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology.
Damien Jacot et al. J Clin Microbiol 2024 e0165123
Chest X-ray evaluation using machine learning to support the early diagnosis of pulmonary TB.
P L Parreira et al. Int J Tuberc Lung Dis 2024 28(4) 171-175
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
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