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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 03/18/2021

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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Non-Genomics Precision Health Scan

Birth Defects and Child Health

Prenatal exposure to air pollutants and childhood atopic dermatitis and allergic rhinitis adopting machine learning approaches: 14-year follow-up birth cohort study.
Huang Yu et al. The Science of the total environment 2021 777145982

Cancer

[Machine learning and multiparametric MRI for early diagnosis of prostate cancer].
Bonekamp D et al. Der Urologe. Ausg. A 2021

Artificial intelligence in precision medicine in hepatology.
Su Tung-Hung et al. Journal of gastroenterology and hepatology 2021 36(3) 569-580

Machine learning for the prediction of bone metastasis in patients with newly diagnosed thyroid cancer.
Liu Wen-Cai et al. Cancer medicine 2021

Artificial intelligence in gastric cancer: a translational narrative review.
Yu Chaoran et al. Annals of translational medicine 2021 9(3) 269

A meta-analysis of Watson for Oncology in clinical application.
Jie Zhou et al. Scientific reports 2021 11(1) 5792

Robust Machine Learning for Colorectal Cancer Risk Prediction and Stratification.
Nartowt Bradley J et al. Frontiers in big data 2021 36

Predictive model for the 5-year survival status of osteosarcoma patients based on the SEER database and XGBoost algorithm.
Jiang Jiuzhou et al. Scientific reports 2021 11(1) 5542

Artificial intelligence for the diagnosis of lymph node metastases in patients with abdominopelvic malignancy: A systematic review and meta-analysis.
Bedrikovetski Sergei et al. Artificial intelligence in medicine 2021 113102022

Development of machine learning model algorithm for prediction of 5-year soft tissue myxoid liposarcoma survival.
Kamalapathy Pramod N et al. Journal of surgical oncology 2021

Development and Validation of a Personalized Survival Prediction Model for Uterine Adenosarcoma: A Population-Based Deep Learning Study.
Qu Wenjie et al. Frontiers in oncology 2021 10623818

The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer.
Ilhan Betul et al. Oral oncology 2021 116105254

Chronic Disease

PDKit: A data science toolkit for the digital assessment of Parkinson's Disease.
Stamate Cosmin et al. PLoS computational biology 2021 17(3) e1008833

Data-driven assessment, contextualisation and implementation of 134 variables in the risk for type 2 diabetes: an analysis of Lifelines, a prospective cohort study in the Netherlands.
van der Meer Thomas P et al. Diabetologia 2021

Clinical notes as prognostic markers of mortality associated with diabetes mellitus following critical care: A retrospective cohort analysis using machine learning and unstructured big data.
De Silva Kushan et al. Computers in biology and medicine 2021 132104305

Using a machine learning approach to investigate factors associated with treatment-resistant depression among adults with chronic non-cancer pain conditions and major depressive disorder.
Shah Drishti et al. Current medical research and opinion 2021 1

A Review of Automated Techniques for Assisting the Early Detection of Alzheimer's Disease with a Focus on EEG.
Perez-Valero Eduardo et al. Journal of Alzheimer's disease : JAD 2021

Toward Machine-Learning-Based Decision Support in Diabetes Care: A Risk Stratification Study on Diabetic Foot Ulcer and Amputation.
Schäfer Zeinab et al. Frontiers in medicine 2021 7601602

Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge.
Schirmer Markus D et al. Medical image analysis 2021 70101972

Deep learning applications for the classification of psychiatric disorders using neuroimaging data: Systematic review and meta-analysis.
Quaak Mirjam et al. NeuroImage. Clinical 2021 30102584

Is artificial intelligence a solution to the myopia pandemic?
Foo Li Lian et al. The British journal of ophthalmology 2021

Episodic Memory-Related Imaging Features as Valuable Biomarkers for the Diagnosis of Alzheimer's Disease: A Multicenter Study Based on Machine Learning.
Shi Yachen et al. Biological psychiatry. Cognitive neuroscience and neuroimaging 2021

Ethical, Legal and Social Issues (ELSI)

AI support for ethical decision-making around resuscitation: proceed with care.
Biller-Andorno Nikola et al. Journal of medical ethics 2021

Governing AI-Driven Health Research: Are IRBs Up to the Task?
Friesen Phoebe et al. Ethics & human research 2021 43(2) 35-42

Many are calling for concrete mechanisms of oversight for health research involving artificial intelligence (AI). In response, institutional review boards (IRBs) are being turned to as a familiar model of governance. Here, we examine the IRB model as a form of ethics oversight for health research that uses AI. We consider the model's origins, analyze the challenges IRBs are facing in the contexts of both industry and academia, and offer concrete recommendations.

General Practice

A Simulated Prospective Evaluation of a Deep Learning Model for Real-Time Prediction of Clinical Deterioration Among Ward Patients.
Shah Parth K et al. Critical care medicine 2021

Machine Learning Assessment of Early Life Factors Predicting Suicide Attempt in Adolescence or Young Adulthood.
Navarro Marie C et al. JAMA network open 2021 4(3) e211450

Open data and injuries in urban areas-A spatial analytical framework of Toronto using machine learning and spatial regressions.
Vaz Eric et al. PloS one 2021 16(3) e0248285

Association of Clinician Diagnostic Performance With Machine Learning-Based Decision Support Systems: A Systematic Review.
Vasey Baptiste et al. JAMA network open 2021 4(3) e211276

Most studies had a low number of participants, were at high or unclear risk of bias, and showed little or no consideration for human factors. Caution should be exercised when estimating the current potential of ML to improve human diagnostic performance, and more comprehensive evaluation should be conducted before deploying ML-based CDSSs in clinical settings.

Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities.
Kusters Remy et al. Frontiers in big data 2021 3577974

Making Big Sense From Big Data.
Hartung Thomas et al. Frontiers in big data 2018 15

The emerging clinical role of wearables: factors for successful implementation in healthcare.
Smuck Matthew et al. NPJ digital medicine 2021 4(1) 45

Artificial intelligence: finding the intersection of predictive modeling and clinical utility.
Ravi Karthik et al. Gastrointestinal endoscopy 2021

Reconciling Statistical and Clinicians' Predictions of Suicide Risk.
Simon Gregory E et al. Psychiatric services (Washington, D.C.) 2021 appips202000214

Assessing the quality of mobile applications in chronic disease management: a scoping review
P Agarwal et all, NPJ Digital Medicine, March 10, 2021

This study highlights the significant variation in quality criteria employed for the assessment of mobile health apps. Future methods for app evaluation will benefit from approaches that leverage the best evidence regarding the clinical impact and behavior change mechanisms while more directly reflecting patient needs when evaluating the quality of apps.

Improving prediction for medical institution with limited patient data: Leveraging hospital-specific data based on multicenter collaborative research network.
Li Jin et al. Artificial intelligence in medicine 2021 113102024

Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools.
Diaz Oliver et al. Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) 2021 8325-37

Exploring the active ingredients of workplace physical and psychological wellbeing programs: a systematic review.
Ryan J C et al. Translational behavioral medicine 2021

The concept of justifiable healthcare and how big data can help us to achieve it.
van Biesen Wim et al. BMC medical informatics and decision making 2021 21(1) 87

ACE: the Advanced Cohort Engine for searching longitudinal patient records.
Callahan Alison et al. Journal of the American Medical Informatics Association : JAMIA 2021

Electronic phenotyping of health outcomes of interest using a linked claims-electronic health record database: Findings from a machine learning pilot project.
Gibson Teresa B et al. Journal of the American Medical Informatics Association : JAMIA 2021

Patient perspectives on acceptability of, and implementation preferences for, use of electronic health records and machine learning to identify suicide risk.
Yarborough Bobbi Jo H et al. General hospital psychiatry 2021 7031-37

Heart, Lung, Blood and Sleep Diseases

Routine Echocardiography and Artificial Intelligence Solutions.
Schuuring Mark J et al. Frontiers in cardiovascular medicine 2021 8648877

Predicting Recurrence for Patients with Ischemic Cerebrovascular Events Based on Process Discovery and Transfer Learning.
Xu Haifeng et al. IEEE journal of biomedical and health informatics 2021 PP

Strengthening the Learning Health System in Cardiovascular Disease Prevention: Time to Leverage Big Data and Digital Solutions.
Wagle Anjali A et al. Current atherosclerosis reports 2021 23(5) 19

Systematic review protocol to assess artificial intelligence diagnostic accuracy performance in detecting acute ischaemic stroke and large-vessel occlusions on CT and MR medical imaging.
Kundeti Srinivasa Rao et al. BMJ open 2021 11(3) e043665

Reviewing the use and quality of machine learning in developing clinical prediction models for cardiovascular disease.
Allan Simon et al. Postgraduate medical journal 2021

Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction.
Khera Rohan et al. JAMA cardiology 2021

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation.
Zhao Yiqing et al. Journal of medical Internet research 2021 23(3) e22951

We developed and validated a machine learning-based algorithm that performed well for identifying incident stroke and for determining type of stroke. The algorithm also performed well on a sample from a general population, further demonstrating its generalizability and potential for adoption by other institutions.

Visualizing and Quantifying Irregular Heart Rate Irregularities to Identify Atrial Fibrillation Events.
Keidar Noam et al. Frontiers in physiology 2021 12637680

MACHINE LEARNING COMPARED TO CONVENTIONAL STATISTICAL MODELS FOR PREDICTING MYOCARDIAL INFARCTION READMISSION AND MORTALITY: A SYSTEMATIC REVIEW.
Cho Sung Min et al. The Canadian journal of cardiology 2021

Infectious Diseases

A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study.
Luellen Eric et al. JMIRx med 2021 1(1) e23582

Added-value of mosquito vector breeding sites from street view images in the risk mapping of dengue incidence in Thailand.
Su Yin Myat et al. PLoS neglected tropical diseases 2021 15(3) e0009122

Temporal analysis of visceral leishmaniasis between 2000 and 2019 in Ardabil Province, Iran: A time-series study using ARIMA model.
Rahmanian Vahid et al. Journal of family medicine and primary care 2021 9(12) 6061-6067

A machine learning approach to predict healthcare-associated infections at intensive care unit admission: findings from the SPIN-UTI project.
Barchitta Martina et al. The Journal of hospital infection 2021

Reproductive Health

Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation.
Velardo Carmelo et al. Journal of medical Internet research 2021 23(3) e21435

Factors Associated with In Vitro Fertilization Live Birth Outcome: A Comparison of Different Classification Methods.
Amini Payam et al. International journal of fertility & sterility 2021 15(2) 128-134


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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