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
Artificial intelligence-powered smartphone application, AICaries, improves at-home dental caries screening in children: Moderated and unmoderated usability test.
Al-Jallad Nisreen et al. PLOS digital health 2022 1(6)
Bedside tracking of functional autonomic age in preterm infants.
Iyer Kartik K et al. Pediatric research 2022
Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischaemic encephalopathy.
Pavel Andreea M et al. Epilepsia 2022
Reporting and risk of bias of prediction models based on machine learning methods in preterm birth: A systematic review.
Yang Qiuyu et al. Acta obstetricia et gynecologica Scandinavica 2022
Prediction model for early childhood caries risk based on behavioral determinants using a machine learning algorithm.
Qu Xing et al. Computer methods and programs in biomedicine 2022 227107221
Feasibility of Establishing an Artificial Intelligence Based Head and Neck Cancer Registry: Experience from a Tertiary Care Hospital.
Gautamjit R K et al. Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India 2022 1-6
Construction and Validation of Early Warning Model of Lung Cancer Based on Machine Learning: A Retrospective Study.
Ye Siyu et al. Technology in cancer research & treatment 2022 2115330338221136724
Differentiation of breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using deep transfer learning based on DenseNet201.
Meng Mingzhu et al. Medicine 2022 101(45) e31214
Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging.
Hsu Shih-Tien et al. BMC medical informatics and decision making 2022 22(1) 298
Use of Machine Learning and Lay Care Coaches to Increase Advance Care Planning Conversations for Patients With Metastatic Cancer.
Gensheimer Michael F et al. JCO oncology practice 2022 OP2200128
Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer: Comparing Five Machine Learning Approaches.
Vesteghem Charles et al. JCO clinical cancer informatics 2022 6e2200054
Leveraging speech and artificial intelligence to screen for early Alzheimer's disease and amyloid beta positivity.
Fristed Emil et al. Brain communications 2022 4(5) fcac231
Screening performances of an 8-item UPSIT Italian version in the diagnosis of Parkinson's disease.
Landolfi Annamaria et al. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology 2022
Multimodal-neuroimaging machine-learning analysis of motor disability in multiple sclerosis.
Rehák Bucková Barbora et al. Brain imaging and behavior 2022
Artificial intelligence in renal pathology: Current status and future.
Feng Chunyue et al. Bosnian journal of basic medical sciences 2022
Novel digital methods for gathering intensive time series data in mental health research: scoping review of a rapidly evolving field.
Schick Anita et al. Psychological medicine 2022 1-11
Guidelines to Establish an Equitable Mobile Health Ecosystem.
Fortuna Karen L et al. Psychiatric services (Washington, D.C.) 2022 appips202200011
Practice of big data and artificial intelligence in epidemic surveillance and containment.
Jiao Zengtao et al. Intelligent medicine 2022
Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.
Zia Adil et al. Scientific reports 2022 12(1) 19885
Artificial Intelligence in Health: Enhancing a Return to Patient-Centered Communication.
Holtz Bree et al. Telemedicine journal and e-health : the official journal of the American Telemedicine Association 2022
Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal.
Vagliano Iacopo et al. Clinical kidney journal 2022 15(12) 2266-2280
A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay.
Stonko David P et al. Surgical innovation 2022 15533506221139965
Artificial intelligence-informed mobile mental health apps for young people: a mixed-methods approach on users' and stakeholders' perspectives.
Götzl Christian et al. Child and adolescent psychiatry and mental health 2022 16(1) 86
Study on the risk of coronary heart disease in middle-aged and young people based on machine learning methods: a retrospective cohort study.
Cao Jiaoyu et al. PeerJ 2022 10e14078
Comparison of conventional scoring systems to machine learning models for the prediction of major adverse cardiovascular events in patients undergoing coronary computed tomography angiography.
Ghorashi Seyyed Mojtaba et al. Frontiers in cardiovascular medicine 2022 9994483
Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction.
Attia Zachi I et al. Nature medicine 2022
Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis.
Din Munaib et al. Journal of neurointerventional surgery 2022
Prediction of the Presence of Ventricular Fibrillation From a Brugada Electrocardiogram Using Artificial Intelligence.
Nakamura Tomofumi et al. Circulation journal : official journal of the Japanese Circulation Society 2022
Multi-center, multi-vendor validation of deep learning-based attenuation correction in SPECT MPI: data from the international flurpiridaz-301 trial.
Hagio Tomoe et al. European journal of nuclear medicine and molecular imaging 2022
Acinetobacter baumannii complex-caused bloodstream infection in ICU during a 12-year period: Predicting fulminant sepsis by interpretable machine learning.
Xu Jun et al. Frontiers in microbiology 2022 131037735
Diagnosing Influenza Infection from Pharyngeal Images using Deep Learning: Machine Learning Approach.
Okiyama Sho et al. Journal of medical Internet research 2022
Meta-learning algorithm development to predict outcomes in patients with hepatitis C virus-related hepatocellular carcinoma.
Lithy Rania M et al. Arab journal of gastroenterology : the official publication of the Pan-Arab Association of Gastroenterology 2022
Developing a machine learning prediction algorithm for early differentiation of urosepsis from urinary tract infection.
Su Mingkuan et al. Clinical chemistry and laboratory medicine 2022
Dynamic gestational week prediction model for pre-eclampsia based on ID3 algorithm.
Li Ziwei et al. Frontiers in physiology 2022 131035726
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:Apr 29, 2024
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