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
Role of artificial intelligence in early detection of congenital heart diseases in neonates.
Haris Ejaz et al. Front Digit Health 2024 51345814
External evaluation of the Dynamic Criticality Index: A machine learning model to predict future need for ICU care in hospitalized pediatric patients.
Anita K Patel et al. PLoS One 2024 19(1) e0288233
Application of Artificial Intelligence in Infant Movement Classification: A Reliability and Validity Study in Infants Who Were Full-Term and Preterm.
Shiang-Chin Lin et al. Phys Ther 2024
Predictors of micronutrient deficiency among children aged 6-23 months in Ethiopia: a machine learning approach.
Leykun Getaneh Gebeye et al. Front Nutr 2024 101277048
Image analysis-based machine learning for the diagnosis of retinopathy of prematurity: A meta-analysis and systematic review.
Yihang Chu et al. Ophthalmol Retina 2024
Classification and Diagnostic Prediction of Colorectal Cancer Mortality Based on Machine Learning Algorithms: A Multicenter National Study.
Gohar Mohammadi et al. Asian Pac J Cancer Prev 2024 25(1) 333-342
Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy.
Omar Falou et al. Sci Rep 2024 14(1) 2340
Interpretable machine learning model for prediction of overall survival in laryngeal cancer.
Rasheed Omobolaji Alabi et al. Acta Otolaryngol 2024 1-7
Real-World Effectiveness of Lung Cancer Screening Using Deep Learning-Based Counterfactual Prediction.
Zheng Feng et al. Stud Health Technol Inform 2024 310419-423
Deep-learning models for image-based gynecological cancer diagnosis: a systematic review and meta- analysis.
Asefa Adimasu Taddese et al. Front Oncol 2024 131216326
Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme.
Gabriel Cerono et al. J Healthc Inform Res 2024 8(1) 1-18
Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center study.
Rui Sun et al. Insights Imaging 2024 15(1) 21
The application value of deep learning in the background of precision medicine in glioblastoma.
Pengyu Chen et al. Sci Prog 2024 107(1) 368504231223353
Editorial: World lung cancer awareness month 2022: artificial intelligence for clinical management of lung cancer.
Parul Agarwal et al. Front Oncol 2024 131351016
From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer.
Satvik Tripathi et al. Diagnostics (Basel) 2024 14(2)
Predicting Phase 1 Lymphoma Clinical Trial Durations Using Machine Learning: An In-Depth Analysis and Broad Application Insights.
Bowen Long et al. Clin Pract 2024 14(1) 69-88
Exploring the Value of MRI Measurement of Hippocampal Volume for Predicting the Occurrence and Progression of Alzheimer's Disease Based on Artificial Intelligence Deep Learning Technology and Evidence-Based Medicine Meta-Analysis.
Jianguo Zhou et al. J Alzheimers Dis 2024
Recommendations for initial diabetic retinopathy screening of diabetic patients using large language model-based artificial intelligence in real-life case scenarios.
Nikhil Gopalakrishnan et al. Int J Retina Vitreous 2024 10(1) 11
Development and deployment of a nationwide predictive model for chronic kidney disease progression in diabetic patients.
Zhiyan Fu et al. Front Nephrol 2024 31237804
Clinical Implementation of Autonomous Artificial Intelligence Systems for Diabetic Eye Exams: Considerations for Success.
Risa M Wolf et al. Clin Diabetes 2024 42(1) 142-149
Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review.
Isabella Veneziani et al. J Pers Med 2024 14(1)
Automatic diagnosis of Parkinson's disease using artificial intelligence base on routine T1-weighted MRI.
Chang Li et al. Front Med (Lausanne) 2024 101303501
Acceptance of Digital Health Technologies in Palliative Care Patients.
Stefan Wicki et al. Palliat Med Rep 2024 5(1) 34-42
Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives.
Molly Bekbolatova et al. Healthcare (Basel) 2024 12(2)
Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study.
Daria Shevtsova et al. JMIR Hum Factors 2024 11e47031
Regulate Artificial Intelligence in Health Care by Prioritizing Patient Outcomes.
John W Ayers et al. JAMA 2024
Large Language Models in Medicine: The Potentials and Pitfalls : A Narrative Review.
Jesutofunmi A Omiye et al. Ann Intern Med 2024
Initial User-Centred Design of an AI-Based Clinical Decision Support System for Primary Care.
Michaela Christina Neff et al. Stud Health Technol Inform 2024 3101051-1055
Development of an individualized risk calculator of treatment resistance in patients with first-episode psychosis (TRipCal) using automated machine learning: a 12-year follow-up study with clozapine prescription as a proxy indicator.
Ting Yat Wong et al. Transl Psychiatry 2024 14(1) 50
Mental Health Counseling From Conversational Content With Transformer-Based Machine Learning.
Zac E Imel et al. JAMA Netw Open 2024 7(1) e2352590
Predicting suicide death after emergency department visits with mental health or self-harm diagnoses.
Gregory E Simon et al. Gen Hosp Psychiatry 2024 8713-19
Clinical Impact of "Real World Data" and Blockchain on Public Health: A Scoping Review.
Virginia Milone et al. Int J Environ Res Public Health 2024 21(1)
Artificial Intelligence for Improved Patient Outcomes-The Pragmatic Randomized Controlled Trial is the Secret Sauce.
Daniel W Byrne et al. Korean J Radiol 2024
A critical moment in machine learning in medicine: on reproducible and interpretable learning.
Olga Ciobanu-Caraus et al. Acta Neurochir (Wien) 2024 166(1) 14
Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients.
Zihan Wang et al. Front Pharmacol 2024 141334439
Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach.
Amir Hossein Behnoush et al. Eur J Med Res 2024 29(1) 76
Digital Health for Myocardial Infarction: Research Topics and Trends.
Melissa Pelly et al. Stud Health Technol Inform 2024 310429-433
Identification of Hypertrophic Cardiomyopathy on Electrocardiographic Images with Deep Learning.
Veer Sangha et al. medRxiv 2024
A Hybrid Model for 30-Day Syncope Prognosis Prediction in the Emergency Department.
Franca Dipaola et al. J Pers Med 2024 14(1)
Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification.
Khaled Abdelrahman et al. Diagnostics (Basel) 2024 14(2)
Advancing Cardiovascular Health Equity Globally Through Digital Technologies.
Oluwabunmi Ogungbe et al. J Am Heart Assoc 2024 13(2) e031237
Automated Identification of Cutaneous Leishmaniasis Lesions Using Deep-Learning-Based Artificial Intelligence.
José Fabrício de Carvalho Leal et al. Biomedicines 2024 12(1)
Rapid and non-invasive detection of cystic echinococcosis in sheep based on serum fluorescence spectrum combined with machine learning algorithms.
Shengke Xu et al. J Biophotonics 2024 e202300357
Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study.
Jialu Li et al. Front Public Health 2024 111282324
Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing.
Ângela Novais et al. J Clin Microbiol 2024 e0121123
Monitoring the Epidemiology of Otitis Using Free-Text Pediatric Medical Notes: A Deep Learning Approach.
Corrado Lanera et al. J Pers Med 2024 14(1)
From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks.
Stan Heidema et al. J Travel Med 2024
Cloud-Integrated Smart Nanomembrane Wearables for Remote Wireless Continuous Health Monitoring of Postpartum Women.
Jared Matthews et al. Adv Sci (Weinh) 2024 e2307609
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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