Genomics and Precision Health Database
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| An epic pushback as U.S. prepares for new era of empowering patient health data HM Krumholz, Stat News, January 27, 2020 |
| The battle for ethical AI at the world’s biggest machine-learning conference E Gibney, Nature News, January 2020 |
| Ethical and Legal Aspects of Ambient Intelligence in Hospitals. Gerke Sara et al. JAMA 2020 Jan  |
| When Deploying Predictive Algorithms, Are Summary Performance Measures Sufficient? Joyce Dan W et al. JAMA psychiatry 2020 Jan  |
| Using machine learning models to classify stroke risk level based on national screening data. Li Xuemeng et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20191386-1390 |
| Deep Learning Based Dosimetry Evaluation at Organs-at-Risk in Esophageal Radiation Treatment Planning. Jiang Dashan et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 2019868-871 |
| Physical activity based classification of serious mental illness group participants in the UK Biobank using ensemble dense neural networks. Zebin Tahmina et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20191251-1254 |
| Hierarchical Pruning for Simplification of Convolutional Neural Networks in Diabetic Retinopathy Classification. Hajabdollahi Mohsen et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 2019970-973 |
| A 3D Deep Residual Convolutional Neural Network for Differential Diagnosis of Parkinsonian Syndromes on 18 F-FDG PET Images. Zhao Yu et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20193531-3534 |
| Deep Learning Based Patient-Specific Classification of Arrhythmia on ECG signal. Zhao Wei et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20191500-1503 |
| Automated Diagnosis of Cardiovascular Disease Through Measurement of Intima Media Thickness Using Deep Neural Networks. Rajasekaran C et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20196636-6639 |
| Privacy-Preserving Artificial Intelligence: Application to Precision Medicine. Vizitiu Anamaria et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20196498-6504 |
| Deep Learning Classification Models Built with Two-step Transfer Learning for Age Related Macular Degeneration Diagnosis. An Guangzhou et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20192049-2052 |
| Early Parkinson's Disease Detection via Touchscreen Typing Analysis using Convolutional Neural Networks. Iakovakis Dimitrios et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20193535-3538 |
| Deep-learning-based fully automatic spine centerline detection in CT data. Jakubicek Roman et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20192407-2410 |
| Classifying Individuals with ASD Through Facial Emotion Recognition and Eye-Tracking. Jiang Ming et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20196063-6068  |
| Machine learning without a feature set for detecting bursts in the EEG of preterm infants. O' Toole John M et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20195799-5802 |
| Deep Neural Network-Based Gait Classification Using Wearable Inertial Sensor Data. Jung Dawoon et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20193624-3628 |
| Deep convolutional neural networks for tongue squamous cell carcinoma classification using Raman spectroscopy. Yu Mingxin et al. Photodiagnosis and photodynamic therapy 2019 Jun 26430-435 |
| A Comparison Study of Algorithms to Detect Drug-Adverse Event Associations: Frequentist, Bayesian, and Machine-Learning Approaches. Pham Minh et al. Drug safety 2019 42(6) 743-750  |
| Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model). Bhattacharya Moumita et al. The American journal of cardiology 2019 123(10) 1681-1689  |
| A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care. Reix Nathalie et al. Clinical chemistry and laboratory medicine 2019 57(6) 901-910 |
| Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network. Ye Hai et al. European radiology 2019 Nov 29(11) 6191-6201 |
| Head and neck squamous cell carcinoma: prediction of cervical lymph node metastasis by dual-energy CT texture analysis with machine learning. Forghani Reza et al. European radiology 2019 Nov 29(11) 6172-6181  |
| Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT. Akagi Motonori et al. European radiology 2019 Nov 29(11) 6163-6171 |
| Artificial Intelligence in Aortic Surgery: The Rise of the Machine. Bashir Mohamad et al. Seminars in thoracic and cardiovascular surgery 31(4) 635-637 |
| Hierarchical Convolutional Neural Networks for Segmentation of Breast Tumors in MRI With Application to Radiogenomics. Zhang Jun et al. IEEE transactions on medical imaging 2019 38(2) 435-447  |
| An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients. Lu Ya et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20195696-5699 |
| Enabling machine learning in X-ray-based procedures via realistic simulation of image formation. Unberath Mathias et al. International journal of computer assisted radiology and surgery 2019 Sep 14(9) 1517-1528 |
| Site specific prediction of atherosclerotic plaque progression using computational biomechanics and machine learning. Kigka Vassiliki I et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20196998-7001 |
| Self-reported and routinely collected electronic healthcare resource-use data for trial-based economic evaluations: the current state of play in England and considerations for the future. Franklin Matthew et al. BMC medical research methodology 2019 19(1) 8 |
| Machine Learning in Modeling High School Sport Concussion Symptom Resolve. Bergeron Michael F et al. Medicine and science in sports and exercise 2019 51(7) 1362-1371  |
| Artificial intelligence and colonoscopy: Current status and future perspectives. Kudo Shin-Ei et al. Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society 2019 Jul 31(4) 363-371 |
| Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective. Mori Yuichi et al. Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society 2019 Jul 31(4) 378-388 |
| Variance Reduction in Neurosurgical Practice: The Case for Analytics-Driven Decision Support in the Era of Big Data. Stopa Brittany M et al. World neurosurgery 2019 Jun 126e190-e195 |
| Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks. Coyner Aaron S et al. Ophthalmology. Retina 2019 3(5) 444-450  |
| Tracing outbreaks with machine learning. Wheeler Nicole E et al. Nature reviews. Microbiology 2019 17(5) 269  |
| Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor. Acharya Sayandeep et al. IEEE journal of biomedical and health informatics 2019 23(3) 1022-1031 |
| SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach. Mousavi Sajad et al. PloS one 2019 14(5) e0216456 |
| Big Data Based m-Health Application to Prevent Health Hazards: A Design Science Framework. Alharbi Ibraheem et al. Telemedicine journal and e-health : the official journal of the American Telemedicine Association 2019 25(4) 326-331 |
| Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing. Schmider Juergen et al. Clinical pharmacology and therapeutics 2019 105(4) 954-961 |
| Evaluation of machine learning algorithms performance for the prediction of early multiple sclerosis from resting-state FMRI connectivity data. Saccà Valeria et al. Brain imaging and behavior 2019 Aug 13(4) 1103-1114 |
| Deep Learning-Based Automatic Endometrium Segmentation and Thickness Measurement for 2D Transvaginal Ultrasound. Hu Szu-Yeu et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 2019993-997 |
| Machine Learning to Identify Predictors of Glycemic Control in Type 2 Diabetes: An Analysis of Target HbA1c Reduction Using Empagliflozin/Linagliptin Data. Del Parigi Angelo et al. Pharmaceutical medicine 2019 Jun 33(3) 209-217 |
| Recognizing Occlusal Caries in Dental Intraoral Images Using Deep Learning. Moutselos K et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20191617-1620 |
| Real-Time Detection of Ureteral Orifice in Urinary Endoscopy Videos Based on Deep Learning. Peng Xin et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20191637-1640 |
| RespNet: A deep learning model for extraction of respiration from photoplethysmogram. Ravichandran Vignesh et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20195556-5559 |
| Hybrid Neural Networks for Mortality Prediction from LDCT Images. Yan Pingkun et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20196243-6246 |
| Detection and Classification of Chronic Total Occlusion lesions using Deep Learning. Liu Xuqing et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 2019828-831 |
| Machine Learning based Human Gait Segmentation with Wearable Sensor Platform. Potluri Sasanka et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 2019588-594 |
| Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants. Hopkins Benjamin S et al. World neurosurgery 2019 Jul 127e436-e442 |
| Adversarially Trained Convolutional Neural Networks for Semantic Segmentation of Ischaemic Stroke Lesion using Multisequence Magnetic Resonance Imaging. Sathish Rachana et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20191010-1013 |
| Evaluation of Facial Pulse Signals using Deep Neural Net Models. Ruminski Jacek et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20193399-3403 |
| Automated Classification of Airborne Pollen using Neural Networks. Schiele Julian et al. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2019 Jul 20194474-4478 |
| Your Fitbit could help health officials predict flu outbreaks in real-time A Kim, CNN, January 2020 |
| SMART Markers: collecting patient-generated health data as a standardized property of health information technology R Sayeed, et al, NPJ Digital Medicine, January 23, 2020 |
| STRIDES initiative NIH Office of Data Science, 2020 |
| Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA. Muscogiuri Giuseppe et al. Atherosclerosis 2019 Dec 29425-32 |
| Identification of a Sixteen-gene Prognostic Biomarker for Lung Adenocarcinoma Using a Machine Learning Method. Ma Baoshan et al. Journal of Cancer 2020 11(5) 1288-1298 |
| Machine learning models for identifying preterm infants at risk of cerebral hemorrhage. Turova Varvara et al. PloS one 2020 15(1) e0227419 |
| Too Many Definitions of Sepsis: Can Machine Learning Leverage the Electronic Health Record to Increase Accuracy and Bring Consensus? Saria Suchi et al. Critical care medicine 2020 Feb 48(2) 137-141 |
| Linking electronic health data in pharmacoepidemiology: Appropriateness and feasibility. Rivera Donna R et al. Pharmacoepidemiology and drug safety 2020 Jan 29(1) 18-29 |
| Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG. Porumb Mihaela et al. Scientific reports 2020 Jan 10(1) 170  |
| A Deep Learning Framework for Assessing Physical Rehabilitation Exercises. Liao Yalin et al. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 2020 Jan |
| Evaluation of the secondary use of electronic health records to detect seasonal, holiday-related, and rare events related to traumatic injury and poisoning. Bergquist Timothy et al. BMC public health 2020 Jan 20(1) 46 |
| Cross-Dataset Evaluation of Deep Learning Networks for Uterine Cervix Segmentation. Guo Peng et al. Diagnostics (Basel, Switzerland) 2020 Jan 10(1) |
| Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India. Nash Madlen et al. Scientific reports 2020 Jan 10(1) 210  |
| Assessment of Balance Control Subsystems by Artificial Intelligence. Ren Peng et al. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 2020 Jan |
| Discovering hidden information in biosignals from patients by artificial intelligence. Yoon Dukyong et al. Korean journal of anesthesiology 2020 Jan |
| Radiomics and Machine Learning in Oral Healthcare. Leite André Ferreira et al. Proteomics. Clinical applications 2020 Jan e1900040  |
| Development and validation of machine learning models to predict gastrointestinal leak and venous thromboembolism after weight loss surgery: an analysis of the MBSAQIP database. Nudel Jacob et al. Surgical endoscopy 2020 Jan |
| Machine learning approaches and databases for prediction of drug-target interaction: a survey paper. Bagherian Maryam et al. Briefings in bioinformatics 2020 Jan  |
| Machine learning can identify newly diagnosed patients with CLL at high risk of infection. Agius Rudi et al. Nature communications 2020 Jan 11(1) 363  |
| Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology? Zhavoronkov Alex et al. Clinical pharmacology and therapeutics 2020 Jan |
| The cytopathologist's role in developing and evaluating artificial intelligence in cytopathology practice. McAlpine Ewen D et al. Cytopathology : official journal of the British Society for Clinical Cytology 2020 Jan |
| Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation. Tiwari Premanand et al. JAMA network open 2020 Jan 3(1) e1919396 |
| Prediction of blood pressure variability using deep neural networks. Koshimizu Hiroshi et al. International journal of medical informatics 2020 Jan 136104067 |
| Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation P Tiwari et al, JAMA Network Open, January 17, 2020 |
| The dark side of digital health I Kickbusch, BMJ, January 2020 |
| mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson’s disease MK Erb et al, NPJ Digital Medicine, January 2020 |
| Study to use artificial intelligence to explore suicide risk P Govern, VUMC Reporter, January 15, 2020 |
| Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study JM Radin et al, Lancet Digital HEalth, January 16, 2020 |
| Machine Learning in Fetal Cardiology: What to Expect. Garcia-Canadilla Patricia et al. Fetal diagnosis and therapy 2020 Jan 1-10 |
| Explainable Artificial Intelligence for Neuroscience: Behavioral Neurostimulation. Fellous Jean-Marc et al. Frontiers in neuroscience 2019 131346 |
| Temporal association of neuropsychological test performance using unsupervised learning reveals a distinct signature of Alzheimer's disease status. Joshi Prajakta S et al. Alzheimer's & dementia (New York, N. Y.) 2019 5964-973  |
| Convolution neural network-based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonance imaging with clinical valuation. Basheera Shaik et al. Alzheimer's & dementia (New York, N. Y.) 2019 5974-986 |
| Feasibility of Multimodal MRI-Based Deep Learning Prediction of High Amino Acid Uptake Regions and Survival in Patients With Glioblastoma. Jeong Jeong-Won et al. Frontiers in neurology 2019 101305 |
| Comparison of the predictive outcomes for anti-tuberculosis drug-induced hepatotoxicity by different machine learning techniques. Lai Nai-Hua et al. Computer methods and programs in biomedicine 2019 Dec 188105307 |
| Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer. Alabi Rasheed Omobolaji et al. International journal of medical informatics 2019 Dec 136104068 |
| Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence. McKinley Richard et al. NeuroImage. Clinical 2019 Dec 25102104 |
| Development and validation of deep learning algorithms for scoliosis screening using back images. Yang Junlin et al. Communications biology 2019 Oct 2(1) 390 |
| Digital phenotyping by consumer wearables identifies sleep-associated markers of cardiovascular disease risk and biological aging. Teo Jing Xian et al. Communications biology 2019 Oct 2(1) 361 |
| Single-modal and multi-modal false arrhythmia alarm reduction using attention-based convolutional and recurrent neural networks. Mousavi Sajad et al. PloS one 2020 15(1) e0226990 |
| Detection of Malignant Melanoma Using Artificial Intelligence: An Observational Study of Diagnostic Accuracy. Phillips Michael et al. Dermatology practical & conceptual 2020 10(1) e2020011 |
| Diastolic Function Evaluation: What Can We Learn From Machine Learning? Kampaktsis Polydoros N et al. JACC. Cardiovascular imaging 2020 Jan 13(1 Pt 2) 336-337 |
| An Intelligent Future for Medical Imaging: A Market Outlook on Artificial Intelligence for Medical Imaging. Alexander Alan et al. Journal of the American College of Radiology : JACR 2020 Jan 17(1 Pt B) 165-170  |
| Deep learning for electronic health records: A comparative review of multiple deep neural architectures. Ayala Solares Jose Roberto et al. Journal of biomedical informatics 2020 Jan 101103337 |
| Machine learning-based mortality prediction of patients undergoing cardiac resynchronization therapy: the SEMMELWEIS-CRT score. Tokodi Márton et al. European heart journal 2020 Jan  |
| Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects. Negassi Misgana et al. World journal of urology 2020 Jan |
| Long short-term memory artificial neural network model for prediction of prostate cancer survival outcomes according to initial treatment strategy: development of an online decision-making support system. Koo Kyo Chul et al. World journal of urology 2020 Jan |
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