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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 02/02/2023

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

Infant Low Birth Weight Prediction Using Graph Embedding Features.
Wasif Khan et al. International journal of environmental research and public health 2023 20(2)

Novel AI-Based Algorithm for the Automated Computation of Coronal Parameters in Adolescent Idiopathic Scoliosis Patients: A Validation Study on 100 Preoperative Full Spine X-Rays.
Clara Berlin et al. Global spine journal 2023 21925682231154543

Predicting no-show appointments in a pediatric hospital in Chile using machine learning.
J Dunstan et al. Health care management science 2023

Distinguishing Exposure to Secondhand and Thirdhand Tobacco Smoke among U.S. Children Using Machine Learning: NHANES 2013-2016.
Ashley L Merianos et al. Environmental science & technology 2023

Quantifying the Severity of Metopic Craniosynostosis Using Unsupervised Machine Learning.
Erin E Anstadt et al. Plastic and reconstructive surgery 2023 151(2) 396-403

Deep learning system to predict the 5-year risk of high myopia using fundus imaging in children.
Li Lian Foo et al. NPJ digital medicine 2023 6(1) 10

Exploring telediagnostic procedures in child neuropsychiatry: addressing ADHD diagnosis and autism symptoms through supervised machine learning.
Silvia Grazioli et al. European child & adolescent psychiatry 2023 1-11

Cancer

Machine-learning prediction model for acute skin toxicity after breast radiation therapy using spectrophotometry.
Savino Cilla et al. Frontiers in oncology 2023 121044358

Artificial intelligence empowers the second-observer strategy for colonoscopy: a randomized clinical trial.
Pu Wang et al. Gastroenterology report 2023 11goac081

The Oesophageal Cancer Multidisciplinary Team: Can Machine Learning Assist Decision-Making?
Navamayooran Thavanesan et al. Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract 2023

A prospective evaluation of breast thermography enhanced by a novel machine learning technique for screening breast abnormalities in a general population of women presenting to a secondary care hospital.
Richa Bansal et al. Frontiers in artificial intelligence 2023 51050803

Survival prediction for stage I-IIIA non-small cell lung cancer using deep learning.
Sunyi Zheng et al. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 2023 109483

Use of Artificial Intelligence for Cancer Clinical Trial Enrolment: A Systematic Review and Meta-Analysis.
Ronald Chow et al. Journal of the National Cancer Institute 2023

Classification Prediction of Breast Cancer Based on Machine Learning.
Hua Chen et al. Computational intelligence and neuroscience 2023 20236530719

A Deep-Learning-Based Artificial Intelligence System for the Pathology Diagnosis of Uterine Smooth Muscle Tumor.
Haiyun Yu et al. Life (Basel, Switzerland) 2023 13(1)

Development and Validation of a Machine Learning Model for Detection and Classification of Tertiary Lymphoid Structures in Gastrointestinal Cancers.
Zhe Li et al. JAMA network open 2023 6(1) e2252553

Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients.
Abdella M Ahmed et al. Biomedical physics & engineering express 2023

A clinical prediction model for predicting the risk of liver metastasis from renal cell carcinoma based on machine learning.
Ziye Wang et al. Frontiers in endocrinology 2023 131083569

Breast cancer detection: Shallow convolutional neural network against deep convolutional neural networks based approach.
Himanish Shekhar Das et al. Frontiers in genetics 2023 131097207

Establishment of prognostic models of adrenocortical carcinoma using machine learning and big data.
Jun Tang et al. Frontiers in surgery 2023 9966307

Artificial Intelligence in Breast Cancer: A Systematic Review on PET Imaging Clinical Applications.
Pierpaolo Alongi et al. Current medical imaging 2023

Evaluation of machine learning algorithms for the prognosis of breast cancer from the Surveillance, Epidemiology, and End Results database.
Ruiyang Wu et al. PloS one 2023 18(1) e0280340

Performance of statistical and machine learning risk prediction models for surveillance benefits and failures in breast cancer survivors.
Yu-Ru Su et al. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2023

OWL: an optimized and independently validated machine learning prediction model for lung cancer screening based on the UK Biobank, PLCO, and NLST populations.
Zoucheng Pan et al. EBioMedicine 2023 88104443

Prediction of bone metastasis in non-small cell lung cancer based on machine learning.
Meng-Pan Li et al. Frontiers in oncology 2023 121054300

Chronic Disease

A machine-learning approach to estimating public intentions to become a living kidney donor in England: Evidence from repeated cross-sectional survey data.
Paul Boadu et al. Frontiers in public health 2023 101052338

In-hospital and home-based long-term monitoring of focal epilepsy with a wearable electroencephalography device. Diagnostic yield and user experience.
Jaiver Macea et al. Epilepsia 2023

Development of Clinical Decision Models for the Prediction of Systemic Lupus Erythematosus and Sjogren's Syndrome Overlap.
Yan Han et al. Journal of clinical medicine 2023 12(2)

A Machine Learning-Based Severity Prediction Tool for the Michigan Neuropathy Screening Instrument.
Fahmida Haque et al. Diagnostics (Basel, Switzerland) 2023 13(2)

Classifying epileptic phase-amplitude coupling in SEEG using complex-valued convolutional neural network.
Chunsheng Li et al. Frontiers in physiology 2023 131085530

Artificial intelligence and inflammatory bowel disease: Where are we going?
Leonardo Da Rio et al. World journal of gastroenterology 2023 29(3) 508-520

Machine learning-based warning model for chronic kidney disease in individuals over 40 years old in underprivileged areas, Shanxi Province.
Wenzhu Song et al. Frontiers in medicine 2023 9930541

Ethical, Legal and Social Issues (ELSI)

Association of Smartphone Use and Digital Addiction with Mental Health, Quality of Life, Motivation and Learning of Medical Students: A Two-Year Follow-Up Study.
Marise Machado de Oliveira et al. Psychiatry 2023 1-14

General Practice

Using a Machine Learning Algorithm to Predict Online Patient Portal Utilization: A Patient Engagement Study.
Ahmed U Otokiti et al. Online journal of public health informatics 2023 14(1) e8

Artificial intelligence and digital medicine for integrated home care services in Italy: Opportunities and limits.
Mariano Cingolani et al. Frontiers in public health 2023 101095001

A Multi-Level Analysis of Individual and Neighborhood Factors Associated with Patient Portal Use among Adult Emergency Department Patients with Multimorbidity.
Hao Wang et al. International journal of environmental research and public health 2023 20(2)

Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?
Giovanni Irmici et al. Diagnostics (Basel, Switzerland) 2023 13(2)

Making machine learning matter to clinicians: model actionability in medical decision-making.
Daniel E Ehrmann et al. NPJ digital medicine 2023 6(1) 7

Artificial intelligence: Its role in dermatopathology.
Shishira R Jartarkar et al. Indian journal of dermatology, venereology and leprology 2023 1-4

Putting undergraduate medical students in AI-CDSS designers' shoes: An innovative teaching method to develop digital health critical thinking.
Rosy Tsopra et al. International journal of medical informatics 2023 171104980

Quality of reporting of randomised controlled trials of artificial intelligence in healthcare: a systematic review.
Rida Shahzad et al. BMJ open 2023 12(9) e061519

Patient similarity and other artificial intelligence machine learning algorithms in clinical decision aid for shared decision-making in the Prevention of Cardiovascular Toxicity (PACT): a feasibility trial design.
Sherry-Ann Brown et al. Cardio-oncology (London, England) 2023 9(1) 7

Prediction of intracranial pressure crises after severe traumatic brain injury using machine learning algorithms.
Dmitriy Petrov et al. Journal of neurosurgery 2023 1-8

Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence-Based Tools in Critical Care: Web-Based Survey Study.
Eric Mlodzinski et al. JMIR perioperative medicine 2023 6e41056

A Sociotechnical Systems Framework for the Application of Artificial Intelligence in Health Care Delivery.
Megan E Salwei et al. Journal of cognitive engineering and decision making 2023 16(4) 194-206

Artificial Intelligence for Evaluation of Emotions behind Face Masks.
Thanapoom Boonipat et al. Plastic and reconstructive surgery 2023 151(2) 354e-356e

Diagnostic quality model (DQM): an integrated framework for the assessment of diagnostic quality when using AI/ML.
Jochen K Lennerz et al. Clinical chemistry and laboratory medicine 2023

Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China.
Xuan Li et al. JMIR public health and surveillance 2023 9e41162

Evaluation of Model-Based PM Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.
Ellen M Considine et al. Environmental science & technology 2023

Heart, Lung, Blood and Sleep Diseases

Fully Automatic Left Ventricle Segmentation Using Bilateral Lightweight Deep Neural Network.
Muhammad Ali Shoaib et al. Life (Basel, Switzerland) 2023 13(1)

Collinearity and Dimensionality Reduction in Radiomics: Effect of Preprocessing Parameters in Hypertrophic Cardiomyopathy Magnetic Resonance T1 and T2 Mapping.
Chiara Marzi et al. Bioengineering (Basel, Switzerland) 2023 10(1)

Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry.
Hyung-Bok Park et al. Clinical cardiology 2023

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.
Artem Zatcepin et al. Zeitschrift fur medizinische Physik 2023

Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups.
Chuan Hong et al. JAMA 2023 329(4) 306-317

Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank.
Rachel Marjorie Wei Wen Tseng et al. BMC medicine 2023 21(1) 28

Performance of cardiovascular disease risk prediction equations in more than 14 000 survivors of cancer in New Zealand primary care: a validation study.
Essa Tawfiq et al. Lancet (London, England) 2023

Machine learning improves mortality prediction in three-vessel disease.
Xinxing Feng et al. Atherosclerosis 2023 3671-7

Rupture discrimination of multiple small (< 7 mm) intracranial aneurysms based on machine learning-based cluster analysis.
Xin Tong et al. BMC neurology 2023 23(1) 45

Multivariate longitudinal data for survival analysis of cardiovascular event prediction in young adults: insights from a comparative explainable study.
Hieu T Nguyen et al. BMC medical research methodology 2023 23(1) 23

Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions.
Hooman H Rashidi et al. Journal of thrombosis and haemostasis : JTH 2023

Infectious Diseases

Spatial distribution and machine learning prediction of sexually transmitted infections and associated factors among sexually active men and women in Ethiopia, evidence from EDHS 2016.
Abdul-Aziz Kebede Kassaw et al. BMC infectious diseases 2023 23(1) 49

Patient-level performance evaluation of a smartphone-based malaria diagnostic application.
Hang Yu et al. Malaria journal 2023 22(1) 33

Big Data Technology in Infectious Diseases Modeling, Simulation and Prediction After the COVID-19 Outbreak: A Survey.
Honghao Shi et al. Intelligent medicine 2023

The efficacy of a novel smart watch on medicine adherence and symptom control of allergic rhinitis patients: Pilot study.
Lisha Li et al. The World Allergy Organization journal 2023 16(1) 100739

Reproductive Health

A Bayesian network model for prediction of low or failed fertilization in assisted reproductive technology based on a large clinical real-world data.
Tian Tian et al. Reproductive biology and endocrinology : RB&E 2023 21(1) 8


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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