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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 12/02/2021

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

External validation of a commercially available deep learning algorithm for fracture detection in children: Fracture detection with a deep learning algorithm.
Dupuis Michel et al. Diagnostic and interventional imaging 2021

Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.
Hasani Navid et al. PET clinics 2021 17(1) 13-29

Deep Learning Approach for Screening Autism Spectrum Disorder in Children with Facial Images and Analysis of Ethnoracial Factors in Model Development and Application.
Lu Angelina et al. Brain sciences 2021 11(11)

Artificial Intelligence Algorithm-Based Computed Tomography Images in the Evaluation of the Curative Effect of Enteral Nutrition after Neonatal High Intestinal Obstruction Operation.
Dong Yanqing et al. Journal of healthcare engineering 2021 20217096286

Artificial Intelligence Supports Decision Making during Open-Chest Surgery of Rare Congenital Heart Defects.
Lo Muzio Francesco Paolo et al. Journal of clinical medicine 2021 10(22)

Cancer

A blind randomized validated convolutional neural network for auto-segmentation of clinical target volume in rectal cancer patients receiving neoadjuvant radiotherapy.
Wu Yijun et al. Cancer medicine 2021

Clinical Application of Artificial Intelligence in PET Imaging of Head and Neck Cancer.
Gharavi Seyed Mohammad H et al. PET clinics 2021 17(1) 65-76

Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions).
Hasani Navid et al. PET clinics 2021 17(1) 145-174

Deep learning-based GTV contouring modeling inter- and intra-observer variability in sarcomas.
Marin Thibault et al. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 2021

Using contrast-enhanced CT and non-contrast-enhanced CT to predict EGFR mutation status in NSCLC patients-a radiomics nomogram analysis.
Yang Xiaoyan et al. European radiology 2021

Using text mining techniques to extract prostate cancer predictive information (Gleason score) from semi-structured narrative laboratory reports in the Gauteng province, South Africa.
Cassim Naseem et al. BMC medical informatics and decision making 2021 21(1) 330

Radiomics analysis allows for precise prediction of silent corticotroph adenoma among non-functioning pituitary adenomas.
Rui Wenting et al. European radiology 2021

Artificial intelligence in oncology: current applications and future perspectives.
Luchini Claudio et al. British journal of cancer 2021

Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now?
Kudo Shin-Ei et al. Translational gastroenterology and hepatology 2021 664

Explainable Artificial Intelligence for Human-Machine Interaction in Brain Tumor Localization.
Esmaeili Morteza et al. Journal of personalized medicine 2021 11(11)

Radiomics and Artificial Intelligence in Uterine Sarcomas: A Systematic Review.
Ravegnini Gloria et al. Journal of personalized medicine 2021 11(11)

Design and Analysis Methods for Trials with AI-Based Diagnostic Devices for Breast Cancer.
Liu Lu et al. Journal of personalized medicine 2021 11(11)

Automation of Lung Ultrasound Interpretation via Deep Learning for the Classification of Normal versus Abnormal Lung Parenchyma: A Multicenter Study.
Arntfield Robert et al. Diagnostics (Basel, Switzerland) 2021 11(11)

Predicting Survival of Patients With Rectal Neuroendocrine Tumors Using Machine Learning: A SEER-Based Population Study.
Cheng Xiaoyun et al. Frontiers in surgery 2021 8745220

Improving ductal carcinoma in situ classification by convolutional neural network with exponential linear unit and rank-based weighted pooling.
Zhang Yu-Dong et al. Complex & intelligent systems 2021 7(3) 1295-1310

Chronic Disease

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review.
Jan Zainab et al. Journal of medical Internet research 2021 23(11) e29749

A Markerless 2D Video, Facial Feature Recognition-Based, Artificial Intelligence Model to Assist With Screening for Parkinson Disease: Development and Usability Study.
Hou Xinyao et al. Journal of medical Internet research 2021 23(11) e29554

Detecting Tonic-Clonic Seizures in Multimodal Biosignal Data From Wearables: Methodology Design and Validation.
Böttcher Sebastian et al. JMIR mHealth and uHealth 2021 9(11) e27674

Research on physical activity variability and changes of metabolic profile in patients with prediabetes using Fitbit activity trackers data.
Bliudzius Antanas et al. Technology and health care : official journal of the European Society for Engineering and Medicine 2021

Digital Biomarkers in Multiple Sclerosis.
Dillenseger Anja et al. Brain sciences 2021 11(11)

Imaging Biomarker Development for Lower Back Pain Using Machine Learning: How Image Analysis Can Help Back Pain.
Gaonkar Bilwaj et al. Methods in molecular biology (Clifton, N.J.) 2021 2393623-640

Improved Deep Convolutional Neural Network to Classify Osteoarthritis from Anterior Cruciate Ligament Tear Using Magnetic Resonance Imaging.
Awan Mazhar Javed et al. Journal of personalized medicine 2021 11(11)

Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson's Disease.
Jakob Verena et al. Sensors (Basel, Switzerland) 2021 21(22)

Hybrid Feature Selection Framework for the Parkinson Imbalanced Dataset Prediction Problem.
Qasim Hayder Mohammed et al. Medicina (Kaunas, Lithuania) 2021 57(11)

Improved Alzheimer's Disease Detection by MRI Using Multimodal Machine Learning Algorithms.
Battineni Gopi et al. Diagnostics (Basel, Switzerland) 2021 11(11)

Deep Learning-Based Artificial Intelligence System for Automatic Assessment of Glomerular Pathological Findings in Lupus Nephritis.
Zheng Zhaohui et al. Diagnostics (Basel, Switzerland) 2021 11(11)

Machine learning-based method for tacrolimus dose predictions in Chinese kidney transplant perioperative patients.
Fu Qun et al. Journal of clinical pharmacy and therapeutics 2021

Ethical, Legal and Social Issues (ELSI)

Advancing health equity with artificial intelligence.
Thomasian Nicole M et al. Journal of public health policy 2021

Demystifying Medico-legal Challenges of Artificial Intelligence Applications in Molecular Imaging and Therapy.
Mezrich Jonathan Lee et al. PET clinics 2021 17(1) 41-49

Ethical Issues of Smart Home-based Elderly Care: A Scoping Review.
Zhu Junhong et al. Journal of nursing management 2021

General Practice

The role of machine learning in cardiovascular pathology.
Glass Carolyn et al. The Canadian journal of cardiology 2021

Artificial intelligence in orthopaedics: A scoping review.
Federer Simon J et al. PloS one 2021 16(11) e0260471

Trustworthy Artificial Intelligence in Medical Imaging.
Hasani Navid et al. PET clinics 2021 17(1) 1-12

Artificial intelligence in dermatology.
Rundle Chandler W et al. Clinics in dermatology 2021 39(4) 657-666

Translating the Machine: Skills that Human Clinicians Must Develop in the Era of Artificial Intelligence.
Aslam Tariq M et al. Ophthalmology and therapy 2021

Deep-learning approach for caries detection and segmentation on dental bitewing radiographs.
Bayrakdar Ibrahim Sevki et al. Oral radiology 2021

An Open-Source, Standard-Compliant, and Mobile Electronic Data Capture System for Medical Research (OpenEDC): Design and Evaluation Study.
Greulich Leonard et al. JMIR medical informatics 2021 9(11) e29176

Opal: an implementation science tool for machine learning clinical decision support in anesthesia.
Bishara Andrew et al. Journal of clinical monitoring and computing 2021

Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.
Kabade Varad et al. Sensors (Basel, Switzerland) 2021 21(22)

Artificial Intelligence, Heuristic Biases, and the Optimization of Health Outcomes: Cautionary Optimism.
Feehan Michael et al. Journal of clinical medicine 2021 10(22)

Machine Learning Model for Outcome Prediction of Patients Suffering from Acute Diverticulitis Arriving at the Emergency Department-A Proof of Concept Study.
Klang Eyal et al. Diagnostics (Basel, Switzerland) 2021 11(11)

Change Management and Digital Innovations in Hospitals of Five European Countries.
Hospodková Petra et al. Healthcare (Basel, Switzerland) 2021 9(11)

Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study.
Levy Joshua J et al. Frontiers in public health 2021 9766707

Impact of Concurrent Use of Artificial Intelligence Tools on Radiologists Reading Time: A Prospective Feasibility Study.
Müller Felix C et al. Academic radiology 2021

Heart, Lung, Blood and Sleep Diseases

An Artificial Intelligence-Based Alarm Strategy Facilitates Management of Acute Myocardial Infarction.
Liu Wen-Cheng et al. Journal of personalized medicine 2021 11(11)

A Sneak-Peek into the Physician's Brain: A Retrospective Machine Learning-Driven Investigation of Decision-Making in TAVR versus SAVR for Young High-Risk Patients with Severe Symptomatic Aortic Stenosis.
Hasimbegovic Ena et al. Journal of personalized medicine 2021 11(11)

Diagnostic Improvements of Deep Learning-Based Image Reconstruction for Assessing Calcification-Related Obstructive Coronary Artery Disease.
Yi Yan et al. Frontiers in cardiovascular medicine 2021 8758793

Diagnostic Accuracy and Generalizability of a Deep Learning-Based Fully Automated Algorithm for Coronary Artery Stenosis Detection on CCTA: A Multi-Centre Registry Study.
Xu Lixue et al. Frontiers in cardiovascular medicine 2021 8707508

Towards Validating the Effectiveness of Obstructive Sleep Apnea Classification from Electronic Health Records Using Machine Learning.
Ramesh Jayroop et al. Healthcare (Basel, Switzerland) 2021 9(11)

Combined Coronary CT-Angiography and TAVR Planning for Ruling Out Significant Coronary Artery Disease: Added Value of Machine-Learning-Based CT-FFR.
Gohmann Robin F et al. JACC. Cardiovascular imaging 2021

Infectious Diseases

Machine Learning Model to Identify Sepsis Patients in the Emergency Department: Algorithm Development and Validation.
Lin Pei-Chen et al. Journal of personalized medicine 2021 11(11)

A Trust-Based Methodology to Evaluate Deep Learning Models for Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images.
Parra Rodrigo et al. Diagnostics (Basel, Switzerland) 2021 11(11)

Data science approaches to confronting the COVID-19 pandemic: a narrative review.
Zhang Qingpeng et al. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 2021 380(2214) 20210127

Event

A machine learning based two-stage clinical decision support system for predicting patients' discontinuation from opioid use disorder treatment: retrospective observational study.
Hasan Md Mahmudul et al. BMC medical informatics and decision making 2021 21(1) 331


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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