Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

Genomics and Precision Health Database


Genomics & Health Impact Scan Database|Search|PHGKB
Last data update: Dec 28, 2020. (Total: 37862 Documents since 2012)
   dataset
Filtered By:
Records 1-30 (of 729 Record(s))
Query Trace: all[original query]>>Non-Genomics Precision Health [Category]
Publication
Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.
Khan Faiz Ahmad et al. The Lancet. Digital health 2020 Nov 2(11) e573-e581
Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study.
Zhu Hongling et al. The Lancet. Digital health 2020 Jul 2(7) e348-e357
Predicting Response to Group Cognitive Behavioral Therapy in Asthma by a Small Number of Abnormal Resting-State Functional Connections.
Zhang Yuqun et al. Frontiers in neuroscience 2020 14575771
Predicting 6-Month Unfavorable Outcome of Acute Ischemic Stroke Using Machine Learning.
Li Xiang et al. Frontiers in neurology 2020 11539509
Image-based Deep Learning in Diagnosing the Etiology of Pneumonia on Pediatric Chest X-rays.
Longjiang E et al. Pediatric pulmonology 2020 Dec
Detection of coronary artery disease in patients with chest pain: An machine learning model based on magnetocardiography parameters.
Xiao Huang et al. Clinical hemorheology and microcirculation 2020 Dec
Developing and evaluating a pediatric asthma severity computable phenotype derived from electronic health records.
Peer Komal et al. The Journal of allergy and clinical immunology 2020 Dec
Improving Clinical Disease Sub-typing and Future Events Prediction through a Chest CT based Deep Learning Approach.
Singla Sumedha et al. Medical physics 2020 Dec
The role of artificial intelligence in identifying asthma in pediatric inpatient setting.
Yu Gang et al. Annals of translational medicine 2020 Nov 8(21) 1367
Machine-learning-based prediction models for high-need high-cost patients using nationwide clinical and claims data.
Osawa Itsuki et al. NPJ digital medicine 2020 Nov 3(1) 148
Ruling In and Ruling Out COVID-19: Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging and Test Data.
D'Ambrosia Christopher et al. Journal of medical Internet research 2020 Nov
A New Wearable System for Home Sleep Apnea Testing, Screening, and Classification.
Manoni Alessandro et al. Sensors (Basel, Switzerland) 2020 Dec 20(24)
Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.
Chernbumroong Saisakul et al. The European respiratory journal 2020 Dec
Identifying Diabetic Macular Edema and Other Retinal Diseases by Optical Coherence Tomography Image and Multiscale Deep Learning.
Zhang Quan et al. Diabetes, metabolic syndrome and obesity : targets and therapy 2020 134787-4800
Neural-Network-Based Diagnosis Using 3-Dimensional Myocardial Architecture and Deformation: Demonstration for the Differentiation of Hypertrophic Cardiomyopathy.
Satriano Alessandro et al. Frontiers in cardiovascular medicine 2020 7584727
Deep neural network-based machine learning reduces the screening workload for systematic review: Investigation based on recent clinical guidelines.
Yamada Tomohide et al. Journal of medical Internet research 2020 Nov
Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?-The IDENTIFY Trial.
Burdick Hoyt et al. Journal of clinical medicine 2020 Nov 9(12)
COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings
M Pahar et al, ARXIV, December 3, 2020
Prediction of hypotension events with physiologic vital sign signatures in the intensive care unit.
Yoon Joo Heung et al. Critical care (London, England) 2020 Nov 24(1) 661
Electroencephalography-Derived Prognosis of Functional Recovery in Acute Stroke Through Machine Learning Approaches.
Chiarelli Antonio Maria et al. International journal of neural systems 2020 Nov 2050067
Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology.
van de Leur Rutger R et al. Arrhythmia & electrophysiology review 2020 Nov 9(3) 146-154
Deep learning algorithm to improve hypertrophic cardiomyopathy mutation prediction using cardiac cine images.
Zhou Hongyu et al. European radiology 2020 Nov
Machine Learning-Based Risk Assessment for Cancer Therapy-Related Cardiac Dysfunction in 4300 Longitudinal Oncology Patients.
Zhou Yadi et al. Journal of the American Heart Association 2020 Nov e019628
Artificial Intelligence and Acute Stroke Imaging.
Soun J E et al. AJNR. American journal of neuroradiology 2020 Nov
Machine learning algorithm for early detection of end-stage renal disease.
Segal Zvi et al. BMC nephrology 2020 Nov 21(1) 518
Comparison of automated and manual DWI-ASPECTS in acute ischemic stroke: total and region-specific assessment.
Cheng XiaoQing et al. European radiology 2020 Nov
Toward Understanding COVID-19 Pneumonia: A Deep-learning-based Approach for Severity Analysis and Monitoring the Disease
M Zandehshahvar et al, MEDRXIV, NOvember 27, 2-2-
A machine learning-based approach for the prediction of periprocedural myocardial infarction by using routine data.
Wang Yao et al. Cardiovascular diagnosis and therapy 2020 Oct 10(5) 1313-1324
Development and Verification of a Digital Twin Patient Model to Predict Specific Treatment Response During the First 24 Hours of Sepsis.
Lal Amos et al. Critical care explorations 2020 Nov 2(11) e0249
Evaluation of incomplete maternal smoking data using machine learning algorithms: a study from the Medical Birth Registry of Norway.
Grøtvedt Liv et al. BMC pregnancy and childbirth 2020 Nov 20(1) 710
TOP