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
Cancerous and Non-Cancerous Brain MRI Classification Method Based on Convolutional Neural Network and Log-Polar Transformation.
Jibon Ferdaus Anam et al. Healthcare (Basel, Switzerland) 2022 10(9)
On an Affordable Approach towards the Diagnosis and Care for Prostate Cancer Patients Using Urine, FTIR and Prediction Machines.
Nsugbe Ejay et al. Diagnostics (Basel, Switzerland) 2022 12(9)
A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images.
Jiang Zijing et al. IEEE/ACM transactions on computational biology and bioinformatics 2022 PP
LiSNet: An AI-based tool for liver imaging staging of hepatocellular carcinoma aggressiveness.
Sun Shu Wen et al. Medical physics 2022
Deep-Learning-Based Real-Time and Automatic Target-to-Background Ratio Calculation in Fluorescence Endoscopy for Cancer Detection and Localization.
Jiang Yang et al. Diagnostics (Basel, Switzerland) 2022 12(9)
Predicting Overall Survival in Patients with Nonmetastatic Gastric Signet Ring Cell Carcinoma: A Machine Learning Approach.
Li Xiaomei et al. Computational and mathematical methods in medicine 2022 20224862376
Radiomics Analysis of Lymph Nodes with Esophageal Squamous Cell Carcinoma Based on Deep Learning.
Chen Li et al. Journal of oncology 2022 20228534262
A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification.
Massafra Raffaella et al. PloS one 2022 17(9) e0274691
Deep Learning for Predicting Distant Metastasis in Patients with Nasopharyngeal Carcinoma Based on Pre-Radiotherapy Magnetic Resonance Imaging.
Hua Hong-Li et al. Combinatorial chemistry & high throughput screening 2022
Deep Learning for Daily Monitoring of Parkinson's Disease Outside the Clinic Using Wearable Sensors.
Atri Roozbeh et al. Sensors (Basel, Switzerland) 2022 22(18)
A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults.
Chen Manting et al. Sensors (Basel, Switzerland) 2022 22(18)
Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data.
Chowdhury Nakib Hayat et al. Journal of personalized medicine 2022 12(9)
Personalized Diagnosis and Treatment for Neuroimaging in Depressive Disorders.
Lee Jongha et al. Journal of personalized medicine 2022 12(9)
Assessing the Impact of Conversational Artificial Intelligence in the Treatment of Stress and Anxiety in Aging Adults: Randomized Controlled Trial.
Danieli Morena et al. JMIR mental health 2022 9(9) e38067
Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques.
Taloni Alessandro et al. International journal of molecular sciences 2022 23(18)
Privacy-Preserving Deep Learning NLP Models for Cancer Registries.
Alawad Mohammed et al. IEEE transactions on emerging topics in computing 2022 9(3) 1219-1230
From real-world electronic health record data to real-world results using artificial intelligence.
Knevel Rachel et al. Annals of the rheumatic diseases 2022
From compute to care: Lessons learned from deploying an early warning system into clinical practice.
Pou-Prom Chloé et al. Frontiers in digital health 2022 4932123
Integration of artificial intelligence into nursing practice.
Abuzaid Mohamed M et al. Health and technology 2022 1-7
Pragmatic AI-augmentation in mental healthcare: Key technologies, potential benefits, and real-world challenges and solutions for frontline clinicians.
Kellogg Katherine C et al. Frontiers in psychiatry 2022 13990370
Critical Analysis of the Current Medical Image-Based Processing Techniques for Automatic Disease Evaluation: Systematic Literature Review.
Rashed Baidaa Mutasher et al. Sensors (Basel, Switzerland) 2022 22(18)
Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey.
Chen Mingyang et al. Frontiers in medicine 2022 9990604
Machine Learning-Based Prediction of Elevated PTH Levels Among the US General Population.
Kato Hajime et al. The Journal of clinical endocrinology and metabolism 2022
Open questions and research gaps for monitoring and updating AI-enabled tools in clinical settings.
Davis Sharon E et al. Frontiers in digital health 2022 4958284
Interplay between Artificial Intelligence and Biomechanics Modeling in the Cardiovascular Disease Prediction.
Li Xiaoyin et al. Biomedicines 2022 10(9)
From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy.
de Lepper Anouk G W et al. Journal of the Royal Society, Interface 2022 19(194) 20220317
A smartphone-interfaced, low-cost colorimetry biosensor for selective detection of bronchiectasis via an artificial neural network.
Sha Mizaj Shabil et al. RSC advances 2022 12(37) 23946-23955
Artificial intelligence to differentiate asthma from COPD in medico-administrative databases.
Joumaa Hassan et al. BMC pulmonary medicine 2022 22(1) 357
A machine learning approach for predicting suicidal ideation in post stroke patients.
Song Seung Il et al. Scientific reports 2022 12(1) 15906
Machine learning-based prediction of in-hospital mortality for post cardiovascular surgery patients admitting to intensive care unit: a retrospective observational cohort study based on a large multi-center critical care database.
Bi Siwei et al. Computer methods and programs in biomedicine 2022 226107115
Deep Learning for Explainable Estimation of Mortality Risk From Myocardial Positron Emission Tomography Images.
Singh Ananya et al. Circulation. Cardiovascular imaging 2022 15(9) e014526
Logistic regression and artificial neural network-based simple predicting models for obstructive sleep apnea by age, sex, and body mass index.
Kuan Yi-Chun et al. Mathematical biosciences and engineering : MBE 2022 19(11) 11409-11421
Identifying nursing sensitive indicators from electronic health records in acute cardiac care - towards intelligent automated assessment of care quality.
von Gerich Hanna et al. Journal of nursing management 2022
Machine Learning Algorithms for Prediction of Survival by Stress Echocardiography in Chronic Coronary Syndromes.
Cortigiani Lauro et al. Journal of personalized medicine 2022 12(9)
How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases?
Hoang-Thi Trieu-Nghi et al. Journal of personalized medicine 2022 12(9)
A Focus on the Role of DSC-PWI Dynamic Radiomics Features in Diagnosis and Outcome Prediction of Ischemic Stroke.
Guo Yingwei et al. Journal of clinical medicine 2022 11(18)
A machine-learning algorithm for diagnosis of multisystem inflammatory syndrome in children and Kawasaki disease in the USA: a retrospective model development and validation study.
Lam Jonathan Y et al. The Lancet. Digital health 2022 4(10) e717-e726
Developing and Validating Clinical Features-Based Machine Learning Algorithms to Predict Influenza Infection in Influenza-like Illness Patients.
Hung Shang-Kai et al. Biomedical journal 2022
A sepsis early warning system is associated with improved patient outcomes.
Kennedy Jason N et al. Cell reports. Medicine 2022 3(9) 100746
Predicting HIV Status among Men Who Have Sex with Men in Bulawayo & Harare, Zimbabwe Using Bio-Behavioural Data, Recurrent Neural Networks, and Machine Learning Techniques.
Chingombe Innocent et al. Tropical medicine and infectious disease 2022 7(9)
Machine Learning-based Prediction of HBV-related Hepatocellular Carcinoma and Detection of Key Candidate Biomarkers.
Kucukakcali Zeynep et al. Medeniyet medical journal 2022 37(3) 255-263
Artificial and human intelligence for early identification of neonatal sepsis.
Sullivan Brynne A et al. Pediatric research 2022
A Turf-Based Feature Selection Technique for Predicting Factors Affecting Human Health during Pandemic.
Saeed Alqahtani et al. Life (Basel, Switzerland) 2022 12(9)
Detection and Visualisation of Pneumoconiosis Using an Ensemble of Multi-Dimensional Deep Features Learned from Chest X-rays.
Devnath Liton et al. International journal of environmental research and public health 2022 19(18)
Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning.
Lee Seung Mi et al. Scientific reports 2022 12(1) 15793
Use of Deep Learning to Detect the Maternal Heart Rate and False Signals on Fetal Heart Rate Recordings.
Boudet Samuel et al. Biosensors 2022 12(9)
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 19, 2024
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