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Genomics & Precision Health Database|Non-Genomics Precision Health Update Archive|Public Health Genomics and Precision Health Knowledge Base (PHGKB) Published on 07/27/2023

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

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Birth Defects and Child Health

Assessing Detection of Children With Suicide-Related Emergencies: Evaluation and Development of Computable Phenotyping Approaches.
Juliet Beni Edgcomb et al. JMIR Ment Health 2023 10e47084

Deep learning in neuroimaging of epilepsy.
Karla Batista García-Ramó et al. Clin Neurol Neurosurg 2023 232107879

Cancer

Machine learning applications for early detection of esophageal cancer: a systematic review.
Farhang Hosseini et al. BMC Med Inform Decis Mak 2023 23(1) 124

A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms.
Tao Chen et al. Front Neurosci 2023 171120781

Study of Patient and Physician Attitudes Toward Automated Prognostic Models for Patients With Metastatic Cancer.
Rachel D Hildebrand et al. JCO Clin Cancer Inform 2023 7e2300023

The predictive value of radiomics-based machine learning for peritoneal metastasis in gastric cancer patients: a systematic review and meta-analysis.
Fan Zhang et al. Front Oncol 2023 131196053

Neural network-based prognostic predictive tool for gastric cardiac cancer: the worldwide retrospective study.
Wei Li et al. BioData Min 2023 16(1) 21

Development of a prediction model for head and neck volume reduction by clinical factors, dose-volume histogram parameters and radiomics in head and neck cancer†.
Miyu Ishizawa et al. J Radiat Res 2023

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.
Xinjie Ning et al. Int J Biochem Cell Biol 2023 106452

Chronic Disease

A survey of artificial intelligence in rheumatoid arthritis.
Jiaqi Wang et al. Rheumatol Immunol Res 2023 4(2) 69-77

Using artificial intelligence to learn optimal regimen plan for Alzheimer's disease.
Kritib Bhattarai et al. J Am Med Inform Assoc 2023

Machine Learning Models to Predict Kidney Stone Recurrence Using 24 Hour Urine Testing and Electronic Health Record-Derived Features.
Patrick Doyle et al. Res Sq 2023

The differential diagnosis value of radiomics-based machine learning in Parkinson's disease: a systematic review and meta-analysis.
Jiaxiang Bian et al. Front Aging Neurosci 2023 151199826

Artificial intelligence and digital solutions for myopia.
Yong Li et al. Taiwan J Ophthalmol 2023 13(2) 142-150

Radiomics for Alzheimer's Disease: Fundamental Principles and Clinical Applications.
Eleni Georgiadou et al. Adv Exp Med Biol 2023 1424297-311

Ethical, Legal and Social Issues (ELSI)

Addressing ethnic and global health inequalities in the era of artificial intelligence healthcare models: a call for responsible implementation.
Mohammad R Ali et al. J R Soc Med 2023 1410768231187734

Translating theory into practice: assessing the privacy implications of concept-based explanations for biomedical AI.
Adriano Lucieri et al. Front Bioinform 2023 31194993

Artificial intelligence in public health: the potential and ethical considerations of artificial intelligence in public health.
I Wayan Gede Suarjana et al. J Public Health (Oxf) 2023

General Practice

Application of artificial intelligence in medical technologies: A systematic review of main trends.
Olga Vl Bitkina et al. Digit Health 2023 920552076231189331

Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study.
Dong Yun Lee et al. J Med Internet Res 2023 25e46165

Individual health-disease phase diagrams for disease prevention based on machine learning.
Kazuki Nakamura et al. J Biomed Inform 2023 104448

The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review.
Joseph Chukwudi Okeibunor et al. Front Public Health 2023 111102185

Adherence of randomised controlled trials using artificial intelligence in ophthalmology to CONSORT-AI guidelines: a systematic review and critical appraisal.
Niveditha Pattathil et al. BMJ Health Care Inform 2023 30(1)

Development and Validation of Two Prediction Models for 72-Hour Mortality in High-Risk Trauma Patients Using a Benchmark Dataset: A Comparative Study of Logistic Regression and Neural Networks Models.
Mehmet Muzaffer Islam et al. Cureus 2023 15(6) e40773

Heart, Lung, Blood and Sleep Diseases

Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives.
Xiaoyu Sun et al. Eur J Med Res 2023 28(1) 242

Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.
Bernhard Föllmer et al. Nat Rev Cardiol 2023

Effective Prediction of Mortality by Heart Disease Among Women in Jordan Using the Chi-Squared Automatic Interaction Detection Model: Retrospective Validation Study.
Salam Bani Hani et al. JMIR Cardio 2023 7e48795

Artificial Intelligence-Powered Technologies for the Management of Vascular Diseases: Building Guidelines and Moving Forward Evidence Generation.
Fabien Lareyre et al. J Endovasc Ther 2023 15266028231187599

Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.
Damini Dey et al. JACC Cardiovasc Imaging 2023

Development and validation of a risk prediction algorithm for recurrent cardiovascular events in the Chinese population: P-CARDIAC.
Ian Wong et al. Br J Gen Pract 2023 73(suppl 1)

The Promise and Risks of mHealth in Heart Failure Care.
Hubert B Haywood et al. J Card Fail 2023

Prognostic implications of machine learning-derived echocardiographic phenotypes in community hypertensive patients.
Anping Cai et al. Clin Exp Hypertens 2023 45(1) 2236334

Development and validation of machine learning algorithms to predict posthypertensive origin in left ventricular hypertrophy.
Maxime Beneyto et al. Arch Cardiovasc Dis 2023

Infectious Diseases

Historical visit attendance as predictor of treatment interruption in South African HIV patients: Extension of a validated machine learning model.
Rachel T Esra et al. PLOS Glob Public Health 2023 3(7) e0002105

Prediction of prognosis in COVID-19 patients using machine learning: A systematic review and meta-analysis.
Ruiyao Chen et al. Int J Med Inform 2023 177105151

Reproductive Health

Deep hybrid model for maternal health risk classification in pregnancy: synergy of ANN and random forest.
Taofeeq Oluwatosin Togunwa et al. Front Artif Intell 2023 61213436


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.
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