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
Deep learning nomogram for predicting neoadjuvant chemotherapy response in locally advanced gastric cancer patients.
Jingjing Zhang et al. Abdom Radiol (NY) 2024
Artificial Intelligence in Cancer Clinical Research: II. Development and Validation of Clinical Prediction Models.
Gary H Lyman et al. Cancer Invest 2024 1-5
Prediction of Lymph Node Metastasis in T1 Colorectal Cancer Using Artificial Intelligence with Hematoxylin and Eosin-Stained Whole-Slide-Images of Endoscopic and Surgical Resection Specimens.
Joo Hye Song et al. Cancers (Basel) 2024 16(10)
Catalyzing Precision Medicine: Artificial Intelligence Advancements in Prostate Cancer Diagnosis and Management.
Ali Talyshinskii et al. Cancers (Basel) 2024 16(10)
A deep learning-based radiomics model for predicting lymph node status from lung adenocarcinoma.
Hui Xie et al. BMC Med Imaging 2024 24(1) 121
Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.
Qingyuan Zhuang et al. BMC Palliat Care 2024 23(1) 124
Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening Cohort.
Sam Ellis et al. Radiol Artif Intell 2024 e230431
The Application of Artificial Intelligence to Cancer Research: A Comprehensive Guide.
Amin Zadeh Shirazi et al. Technol Cancer Res Treat 2024 2315330338241250324
A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders.
Assaf Zadka et al. NPJ Digit Med 2024 7(1) 142
External Validation of a Machine Learning Model for Schizophrenia Classification.
Yupeng He et al. J Clin Med 2024 13(10)
Prediction of Cognitive Impairment Risk among Older Adults: A Machine-Learning Based Comparative Study and Model Development.
Jianwei Li et al. Dement Geriatr Cogn Disord 2024
Risk prediction models of depression in older adults with chronic diseases.
Ying Zheng et al. J Affect Disord 2024 359182-188
Application of Artificial Intelligence Methods on Osteoporosis Classification with Radiographs-A Systematic Review.
Ren Wei Liu et al. Bioengineering (Basel) 2024 11(5)
Physical frailty identification using machine learning to explore the 5-item FRAIL scale, Cardiovascular Health Study index, and Study of Osteoporotic Fractures index.
Chen-Cheng Yang et al. Front Public Health 2024 121303958
Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm.
Rhian Daniel et al. Lancet Digit Health 2024 6(6) e386-e395
Actual Clinical Practice Assessment: A Rapid and Easy-to-Use Tool for Evaluating Cognitive Decline Equivalent to Dementia.
Takayuki Asano et al. Cureus 2024 16(4) e58781
Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges.
Aisling O'Leary et al. Sensors (Basel) 2024 24(10)
A machine-learning approach to model risk and protective factors of vulnerability to depression.
June M Liu et al. J Psychiatr Res 2024 175374-380
Natural language processing systems for extracting information from electronic health records about activities of daily living. A systematic review.
Yvonne Wieland-Jorna et al. JAMIA Open 2024 7(2) ooae044
Development and evaluation of a deep learning framework for the diagnosis of malnutrition using a 3D facial points cloud: A cross-sectional study.
Xue Wang et al. JPEN J Parenter Enteral Nutr 2024
Predicting the Outcome and Survival of Patients with Spinal Cord Injury using Machine Learning Algorithms; A Systematic Review.
Mohammad Amin Habibi et al. World Neurosurg 2024
Consolidated Health Economic Evaluation Reporting Standards for Interventions that use Artificial Intelligence (CHEERS-AI).
Jamie Elvidge et al. Value Health 2024
The AI Future of Emergency Medicine.
Robert J Petrella et al. Ann Emerg Med 2024
Clinical Applications of Artificial Intelligence in Medical Imaging and Image Processing-A Review.
Rafal Obuchowicz et al. Cancers (Basel) 2024 16(10)
Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project.
Robert West et al. Wellcome Open Res 2024 8452
The potential use of artificial intelligence for venous thromboembolism prophylaxis and management: clinician and healthcare informatician perspectives.
Barbara D Lam et al. Sci Rep 2024 14(1) 12010
Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients.
Chua Ming et al. J Pers Med 2024 14(5)
Machine learning prediction of one-year mortality after percutaneous coronary intervention in acute coronary syndrome patients.
Kaveh Hosseini et al. Int J Cardiol 2024 409132191
Development and validation of risk prediction model for recurrent cardiovascular events among Chinese: the Personalized CARdiovascular DIsease risk Assessment for Chinese model.
Yekai Zhou et al. Eur Heart J Digit Health 2024 5(3) 363-370
Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study.
Siyuan Wang et al. J Clin Hypertens (Greenwich) 2024
Predictors of 30-day readmission based on machine learning in patients with heart failure: an essential assessment for precision care.
Bei Dou et al. Eur J Cardiovasc Nurs 2024
A machine learning approach to classifying New York Heart Association (NYHA) heart failure.
Krystian Jandy et al. Sci Rep 2024 14(1) 11496
Automatic detection of cardiac conditions from photos of electrocardiogram captured by smartphones.
Chun-Ka Wong et al. Heart 2024
A Machine Learning-Based Mortality Prediction Model for Patients with Chronic Hepatitis C Infection: An Exploratory Study.
Abdullah M Al Alawi et al. J Clin Med 2024 13(10)
Application of boosted trees to the prognosis prediction of COVID-19.
Sajjad Molaei et al. Health Sci Rep 2024 7(5) e2104
Artificial Intelligence in the Management of Women with Endometriosis and Adenomyosis: Can Machines Ever Be Worse Than Humans?
Giulia Emily Cetera et al. J Clin Med 2024 13(10)
Predictive Modelling of Postpartum Haemorrhage Using Early Risk Factors: A Comparative Analysis of Statistical and Machine Learning Models.
Shannon Holcroft et al. Int J Environ Res Public Health 2024 21(5)
Evaluating the performance of an AI-powered VBAC prediction system within a decision-aid birth choice platform for shared decision-making.
Cherng Chia Yang et al. Digit Health 2024 1020552076241257014
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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