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
Prediction of extubation failure in the paediatric cardiac ICU using machine learning and high-frequency physiologic data.
Rooney Sydney R et al. Cardiology in the young 2021 1-8
Comparison of Multivariable Logistic Regression and Machine Learning Models for Predicting Bronchopulmonary Dysplasia or Death in Very Preterm Infants.
Khurshid Faiza et al. Frontiers in pediatrics 2021 9759776
Deep-Learning Approach to Predict Survival Outcomes Using Wearable Actigraphy Device Among End-Stage Cancer Patients.
Yang Tien Yun et al. Frontiers in public health 2021 9730150
Decision Support System for Breast Cancer Detection Using Biomarker Indicators.
Vergis Spiridon et al. Advances in experimental medicine and biology 2022 133813-19
Clinical Applications of Artificial Intelligence, Machine Learning, and Deep Learning in the Imaging of Gliomas: A Systematic Review.
Alhasan Ayman S et al. Cureus 2021 13(11) e19580
Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer.
Jeong Seri et al. Cancer control : journal of the Moffitt Cancer Center 2021 2810732748211033401
Characterizing Malignant Melanoma Clinically Resembling Seborrheic Keratosis Using Deep Knowledge Transfer.
Spyridonos Panagiota et al. Cancers 2021 13(24)
Imaging-based Machine-learning Models to Predict Clinical Outcomes and Identify Biomarkers in Pancreatic Cancer: A Scoping Review.
Janssen Boris V et al. Annals of surgery 2021
[Research status and prospect of artificial intelligence technology in the diagnosis of urinary system tumors].
Liu Kun et al. Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi 2021 38(6) 1219-1228
MRI-Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma.
Liao Hai et al. Journal of magnetic resonance imaging : JMRI 2021
Wearable Technology to Increase Self-Awareness of Low Back Pain: A Survey of Technology Needs among Health Care Workers.
Ferrone Andrea et al. Sensors (Basel, Switzerland) 2021 21(24)
Accelerating Hyperparameter Tuning in Machine Learning for Alzheimer's Disease With High Performance Computing.
Zhang Fan et al. Frontiers in artificial intelligence 2021 4798962
Remote Monitoring Systems for Patients With Chronic Diseases in Primary Health Care: Systematic Review.
Peyroteo Mariana et al. JMIR mHealth and uHealth 2021 9(12) e28285
Machine learning applications to differentiate comorbid functional seizures and epilepsy from pure functional seizures.
Asadi-Pooya Ali A et al. Journal of psychosomatic research 2021 153110703
A Machine Learning-Based Aging Measure Among Middle-Aged and Older Chinese Adults: The China Health and Retirement Longitudinal Study.
Cao Xingqi et al. Frontiers in medicine 2021 8698851
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
Jacobsohn Gwen Costa et al. Healthcare (Amsterdam, Netherlands) 2021 10(1) 100598
Automated Classification of Normal Control and Early-Stage Dementia Based on Activities of Daily Living (ADL) Data Acquired from Smart Home Environment.
Kwon Lee-Nam et al. International journal of environmental research and public health 2021 18(24)
A Case for The Use of Artificial Intelligence in Glaucoma Assessment.
Schuman Joel S et al. Ophthalmology. Glaucoma 2021
Active deep learning to detect cognitive concerns in electronic health records.
Magdamo Colin G et al. Alzheimer's & dementia : the journal of the Alzheimer's Association 2021 17 Suppl 11e055362
Highway to (Digital) Surveillance: When Are Clients Coerced to Share Their Data with Insurers?
Loi Michele et al. Journal of business ethics : JBE 2021 175(1) 7-19
FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies.
Ebrahimian Shadi et al. Academic radiology 2021
The Cybersecurity and the Care Robots: A Viewpoint on the Open Problems and the Perspectives.
Giansanti Daniele et al. Healthcare (Basel, Switzerland) 2021 9(12)
A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study.
Yao Li-Hung et al. Journal of medical Internet research 2021 23(12) e27008
Validation of a Multimodal EEG-Based Index to Aid in Diagnosing and Tracking Concussion Among Athletes.
Bazarian Jeffrey J et al. Neurology 2021 98(1 Supplement 1) S20-S21
Development and validation pathways of artificial intelligence tools evaluated in randomised clinical trials.
Siontis George C M et al. BMJ health & care informatics 2021 28(1)
Machine Learning Algorithms Predict Achievement of Clinically Significant Outcomes Following Orthopaedic Surgery: A Systematic Review.
Kunze Kyle N et al. Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association 2021
Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances.
Tohira Hideo et al. Informatics for health & social care 2021 1-11
Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.
Jin Kwang Nam et al. European radiology 2022
Electronic health record machine learning model predicts trauma inpatient mortality in real time: A validation study.
Mou Zongyang et al. The journal of trauma and acute care surgery 2021 92(1) 74-80
Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study.
Jones Catherine M et al. BMJ open 2021 11(12) e052902
Guidance for using artificial intelligence for title and abstract screening while conducting knowledge syntheses.
Hamel Candyce et al. BMC medical research methodology 2021 21(1) 285
Detecting Receptivity for mHealth Interventions in the Natural Environment.
Mishra Varun et al. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies 2021 5(2)
NextGen Public Health Surveillance and the Internet of Things (IoT).
Sahu Kirti Sundar et al. Frontiers in public health 2021 9756675
Reduced Risk of Reoperations With Modern Deep Brain Stimulator Systems: Big Data Analysis From a United States Claims Database.
Wu Chengyuan et al. Frontiers in neurology 2021 12785280
Implementation and Evaluation of an Artificial Intelligence Driven Simulation to Improve Resident Communication with Primary Care Providers.
Merritt Conor et al. Academic pediatrics 2021
Machine learning methods applied to triage in emergency services: A systematic review.
Sánchez-Salmerón Rocío et al. International emergency nursing 2021 60101109
Health Care Analytics With Time-Invariant and Time-Variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study.
Chua Horng-Ruey et al. Journal of medical Internet research 2021 23(12) e30805
The Clinical Course of Alcohol Use Disorder Depicted by Digital Biomarkers.
Zetterström Andreas et al. Frontiers in digital health 2021 3732049
Does Artificial Intelligence Make Clinical Decision Better? A Review of Artificial Intelligence and Machine Learning in Acute Kidney Injury Prediction.
Lee Tao Han et al. Healthcare (Basel, Switzerland) 2021 9(12)
The Dilemma of Analyzing Physical Activity and Sedentary Behavior with Wrist Accelerometer Data: Challenges and Opportunities.
Gao Zan et al. Journal of clinical medicine 2021 10(24)
Predicting Prolonged Length of ICU Stay through Machine Learning.
Wu Jingyi et al. Diagnostics (Basel, Switzerland) 2021 11(12)
Modeling factors critical for implementation of precision medicine at health systems-level: an IRT approach.
Mogaka John Jo et al. American journal of translational research 2021 13(11) 12557-12574
Artificial Intelligence empowered recruitment for clinical trials.
Linz Nicklas et al. Alzheimer's & dementia : the journal of the Alzheimer's Association 2021 17 Suppl 8e050304
Implementing Machine Learning in Interventional Cardiology: The Benefits Are Worth the Trouble.
Ben Ali Walid et al. Frontiers in cardiovascular medicine 2021 8711401
Online Automatic Diagnosis System of Cardiac Arrhythmias Based on MIT-BIH ECG Database.
Yan Wei et al. Journal of healthcare engineering 2021 20211819112
Machine Learning Approach to Classify Cardiovascular Disease in Patients With Nonalcoholic Fatty Liver Disease in the UK Biobank Cohort.
Sharma Divya et al. Journal of the American Heart Association 2021 e022576
Evaluation of Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction Based on CT Features of Deep Learning.
Zhang Wei et al. Computational and mathematical methods in medicine 2021 20217936548
Technical and practical aspects of artificial intelligence in cardiology.
Bohm A et al. Bratislavske lekarske listy 2021 123(1) 16-21
Continuous Remote Patient Monitoring: Evaluation of the Heart Failure Cascade Soft Launch.
Chi Wei Ning et al. Applied clinical informatics 2021 12(5) 1161-1173
Predicting atrial fibrillation episodes with rapid ventricular rates associated with low levels of activity.
Li Zhi et al. BMC medical informatics and decision making 2021 21(1) 364
Inter-patient arrhythmia classification with improved deep residual convolutional neural network.
Li Yuanlu et al. Computer methods and programs in biomedicine 2021 214106582
A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.
Alon Leeor et al. Scientific reports 2021 11(1) 24222
Automated Scoring of Respiratory Events in Sleep with a Single Effort Belt and Deep Neural Networks.
Nassi Thijs-Enagnon et al. IEEE transactions on bio-medical engineering 2021 PP
Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review.
Alamgir Asma et al. JMIR medical informatics 2021 9(12) e30798
Unseen Artificial Intelligence-Deep Learning Paradigm for Segmentation of Low Atherosclerotic Plaque in Carotid Ultrasound: A Multicenter Cardiovascular Study.
Jain Pankaj K et al. Diagnostics (Basel, Switzerland) 2021 11(12)
A Prediction Model of Incident Cardiovascular Disease in Patients with Sleep-Disordered Breathing.
Park Jong-Uk et al. Diagnostics (Basel, Switzerland) 2021 11(12)
Wearable Devices, Smartphones, and Interpretable Artificial Intelligence in Combating COVID-19.
Hijazi Haytham et al. Sensors (Basel, Switzerland) 2021 21(24)
Spatial modeling of zoonotic cutaneous leishmaniasis with regard to potential environmental factors using ANFIS and PCA-ANFIS methods.
Babaie Elnaz et al. Acta tropica 2021 106296
Imaging Manifestations and Evaluation of Postoperative Complications of Bone and Joint Infections under Deep Learning.
Mao Wei et al. Journal of healthcare engineering 2021 20216112671
An Interpretable Early Dynamic Sequential Predictor for Sepsis-Induced Coagulopathy Progression in the Real-World Using Machine Learning.
Cui Ruixia et al. Frontiers in medicine 2021 8775047
Clinical Applicable AI System Based on Deep Learning Algorithm for Differentiation of Pulmonary Infectious Disease.
Zhang Yu-Han et al. Frontiers in medicine 2021 8753055
Evaluation of an artificial intelligence (AI) system to detect tuberculosis on chest X-ray at a pilot active screening project in Guangdong, China in 2019.
Liao Qinghua et al. Journal of X-ray science and technology 2021
Using Artificial Intelligence-based models to predict the risk of Mucormycosis among COVID-19 Survivors: An Experience from a public hospital in India.
Syed-Abdul Shabbir et al. The Journal of infection 2021
The Clinical Value of Explainable Deep Learning for Diagnosing Fungal Keratitis Using in vivo Confocal Microscopy Images.
Xu Fan et al. Frontiers in medicine 2021 8797616
Detection of Preventable Fetal Distress During Labor From Scanned Cardiotocogram Tracings Using Deep Learning.
Frasch Martin G et al. Frontiers in pediatrics 2021 9736834
Early gestational profiling of oxidative stress and angiogenic growth mediators as predictive, preventive and personalised (3P) medical approach to identify suboptimal health pregnant mothers likely to develop preeclampsia.
Anto Enoch Odame et al. The EPMA journal 2021 12(4) 517-534
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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