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
Identifying Children at Readmission Risk: At-Admission versus Traditional At-Discharge Readmission Prediction Model.
Symum Hasan et al. Healthcare (Basel, Switzerland) 2021 9(10)
Machine Learning Algorithms to Predict Mortality of Neonates on Mechanical Intubation for Respiratory Failure.
Hsu Jen-Fu et al. Biomedicines 2021 9(10)
The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems.
Tisdale Ainslie et al. Orphanet journal of rare diseases 2021 16(1) 429
Investigation of a dysmorphic facial phenotype in patients with Gaucher disease types 2 and 3.
Daykin Emily et al. Molecular genetics and metabolism 2021
Use of Machine Learning and Statistical Algorithms to Predict Hospital Length of Stay Following Colorectal Cancer Resection: A South African Pilot Study.
Achilonu Okechinyere J et al. Frontiers in oncology 2021 11644045
Tracking cancer lesions on surgical samples of gastric cancer by artificial intelligent algorithms.
Yang Ruixin et al. Journal of Cancer 2021 12(21) 6473-6483
An integrated AI model to improve diagnostic accuracy of ultrasound and output known risk features in suspicious thyroid nodules.
Wang Juan et al. European radiology 2021
Machine Learning Models Cannot Replace Screening Colonoscopy for the Prediction of Advanced Colorectal Adenoma.
Semmler Georg et al. Journal of personalized medicine 2021 11(10)
DermIA: Machine Learning to Improve Skin Cancer Screening.
Shoen Ezra et al. Journal of digital imaging 2021
Artificial Intelligence-Based Segmentation of Residual Tumor in Histopathology of Pancreatic Cancer after Neoadjuvant Treatment.
Janssen Boris V et al. Cancers 2021 13(20)
Detection Accuracy and Latency of Colorectal Lesions with Computer-Aided Detection System Based on Low-Bias Evaluation.
Matsui Hiroaki et al. Diagnostics (Basel, Switzerland) 2021 11(10)
Automatic Recognition of Colon and Esophagogastric Cancer with Machine Learning and Hyperspectral Imaging.
Collins Toby et al. Diagnostics (Basel, Switzerland) 2021 11(10)
Can machine learning-based analysis of multiparameter MRI and clinical parameters improve the performance of clinically significant prostate cancer diagnosis?
Peng Tao et al. International journal of computer assisted radiology and surgery 2021
A Combined Radiomics and Machine Learning Approach to Distinguish Clinically Significant Prostate Lesions on a Publicly Available MRI Dataset.
Donisi Leandro et al. Journal of imaging 2021 7(10)
Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging.
Abdel Razek Ahmed Abdel Khalek et al. Insights into imaging 2021 12(1) 152
'Artificial intelligence in Barrett's Esophagus'.
Hamade Nour et al. Therapeutic advances in gastrointestinal endoscopy 2021 1426317745211049964
[Automatic Quantification of Breast Density from Mammography Using Deep Learning].
Inoue Kenichi et al. Nihon Hoshasen Gijutsu Gakkai zasshi 2021 77(10) 1165-1172
Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images.
Dov David et al. Archives of pathology & laboratory medicine 2021
Application of Artificial Intelligence in Early Gastric Cancer Diagnosis.
Xiao Zili et al. Digestion 2021 1-7
Identifying Individualized Risk Profiles for Radiotherapy-Induced Lymphopenia Among Patients With Esophageal Cancer Using Machine Learning.
Zhu Cong et al. JCO clinical cancer informatics 2021 51044-1053
Machine Learning Techniques for Personalised Medicine Approaches in Immune-Mediated Chronic Inflammatory Diseases: Applications and Challenges.
Peng Junjie et al. Frontiers in pharmacology 2021 12720694
Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review.
D'Antoni Federico et al. International journal of environmental research and public health 2021 18(20)
A Machine Learning Application to Predict Early Lung Involvement in Scleroderma: A Feasibility Evaluation.
Murdaca Giuseppe et al. Diagnostics (Basel, Switzerland) 2021 11(10)
Applications of Machine Learning in Bone and Mineral Research.
Kong Sung Hye et al. Endocrinology and metabolism (Seoul, Korea) 2021
Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative.
Tack Alexander et al. PloS one 2021 16(10) e0258855
Intelligent type 2 diabetes risk prediction from administrative claim data.
Uddin Shahadat et al. Informatics for health & social care 2021 1-15
Combined automated screening for age-related macular degeneration and diabetic retinopathy in primary care settings.
Bhuiyan Alauddin et al. Annals of eye science 2021 6
ARTEFICIAL INTELLIGENCE IN DIABETIC RETINOPATHY SCREENING. A REVIEW.
Stranák Z et al. Ceska a slovenska oftalmologie : casopis Ceske oftalmologicke spolecnosti a Slovenske oftalmologicke spolecnosti 2021 77(5) 224-231
Bone Strain Index predicts fragility fracture in osteoporotic women: an artificial intelligence-based study.
Ulivieri Fabio Massimo et al. European radiology experimental 2021 5(1) 47
Towards teaching analytics: a contextual model for analysis of students' evaluation of teaching through text mining and machine learning classification.
Okoye Kingsley et al. Education and information technologies 2021 1-43
A Survival Guide for the Rapid Transition to a Fully Digital Workflow: The "Caltagirone Example".
Fraggetta Filippo et al. Diagnostics (Basel, Switzerland) 2021 11(10)
Using neural networks to support high-quality evidence mapping.
Røst Thomas B et al. BMC bioinformatics 2021 22(Suppl 11) 496
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.
Andaur Navarro Constanza L et al. BMJ (Clinical research ed.) 2021 375n2281
Harnessing Machine Learning to Personalize Web-Based Health Care Content.
Guni Ahmad et al. Journal of medical Internet research 2021 23(10) e25497
Deep learning evaluation of biomarkers from echocardiogram videos.
Hughes J Weston et al. EBioMedicine 2021 73103613
Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram.
Vaid Akhil et al. JACC. Cardiovascular imaging 2021
Prediction of all-cause mortality in coronary artery disease patients with atrial fibrillation based on machine learning models.
Liu Xinyun et al. BMC cardiovascular disorders 2021 21(1) 499
Development of the Hypertension Index Model in General Adult Using the Korea National Health and Nutritional Examination Survey and the Korean Genome and Epidemiology Study.
Seo Myung-Jae et al. Journal of personalized medicine 2021 11(10)
Electrocardiogram Quality Assessment with a Generalized Deep Learning Model Assisted by Conditional Generative Adversarial Networks.
Zhou Xue et al. Life (Basel, Switzerland) 2021 11(10)
Could a Multi-Marker and Machine Learning Approach Help Stratify Patients with Heart Failure?
Lotierzo Manuela et al. Medicina (Kaunas, Lithuania) 2021 57(10)
Artificial Intelligence Identifies an Urgent Need for Peripheral Vascular Intervention by Multiplexing Standard Clinical Parameters.
Sonnenschein Kristina et al. Biomedicines 2021 9(10)
A Machine Learning Approach for Chronic Heart Failure Diagnosis.
Plati Dafni K et al. Diagnostics (Basel, Switzerland) 2021 11(10)
Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms.
Lo Yu-Tai et al. BMC medical informatics and decision making 2021 21(1) 288
Management and Treatment of Patients With Obstructive Sleep Apnea Using an Intelligent Monitoring System Based on Machine Learning Aiming to Improve Continuous Positive Airway Pressure Treatment Compliance: Randomized Controlled Trial.
Turino Cecilia et al. Journal of medical Internet research 2021 23(10) e24072
A language-matching model to improve equity and efficiency of COVID-19 contact tracing.
Lu Lisa et al. Proceedings of the National Academy of Sciences of the United States of America 2021 118(43)
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:Mar 28, 2024
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