npj Digital Medicine

Papers
(The TQCC of npj Digital Medicine is 26. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-03-01 to 2024-03-01.)
ArticleCitations
The future of digital health with federated learning859
The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database504
Deep learning-enabled medical computer vision447
Machine learning-based prediction of COVID-19 diagnosis based on symptoms312
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis284
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines253
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction228
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)224
Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare210
Digital inclusion as a social determinant of health193
Machine learning for medical imaging: methodological failures and recommendations for the future177
Chatbots in the fight against the COVID-19 pandemic173
Methods in predictive techniques for mental health status on social media: a critical review173
A short guide for medical professionals in the era of artificial intelligence170
Digitizing clinical trials164
Do as AI say: susceptibility in deployment of clinical decision-aids157
Applications of digital health for public health responses to COVID-19: a systematic scoping review of artificial intelligence, telehealth and related technologies156
Challenges for the evaluation of digital health solutions—A call for innovative evidence generation approaches151
The future of sleep health: a data-driven revolution in sleep science and medicine141
The emerging clinical role of wearables: factors for successful implementation in healthcare141
Assessment of physiological signs associated with COVID-19 measured using wearable devices140
Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency138
Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review135
Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study133
A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases132
Second opinion needed: communicating uncertainty in medical machine learning131
Automated abnormality classification of chest radiographs using deep convolutional neural networks129
Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research126
A large language model for electronic health records126
Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers125
The need for a system view to regulate artificial intelligence/machine learning-based software as medical device114
U-Sleep: resilient high-frequency sleep staging114
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium109
Germany’s digital health reforms in the COVID-19 era: lessons and opportunities for other countries107
Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery106
Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities105
Patient apprehensions about the use of artificial intelligence in healthcare105
Full-waveform inversion imaging of the human brain103
A framework for digital health equity103
The imperative for regulatory oversight of large language models (or generative AI) in healthcare99
Digital medicine and the curse of dimensionality98
What do medical students actually need to know about artificial intelligence?96
Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-1994
Interpretable survival prediction for colorectal cancer using deep learning93
Developing a delivery science for artificial intelligence in healthcare88
Deep representation learning of electronic health records to unlock patient stratification at scale86
Generating high-fidelity synthetic patient data for assessing machine learning healthcare software84
Readiness for voice assistants to support healthcare delivery during a health crisis and pandemic84
The potential of artificial intelligence to improve patient safety: a scoping review83
Actionable health app evaluation: translating expert frameworks into objective metrics82
Tracking COVID-19 using online search82
A machine learning approach predicts future risk to suicidal ideation from social media data81
Predicting COVID-19 mortality with electronic medical records80
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department80
Presenting machine learning model information to clinical end users with model facts labels80
Characteristics and challenges of the clinical pipeline of digital therapeutics80
Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation80
Multimodal machine learning in precision health: A scoping review79
Natural language processing applied to mental illness detection: a narrative review79
A systematic review of smartphone-based human activity recognition methods for health research78
Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use78
Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement76
Preventive digital mental health interventions for children and young people: a review of the design and reporting of research73
Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare72
Pan-cancer diagnostic consensus through searching archival histopathology images using artificial intelligence71
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging70
Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations68
Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians?68
Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data68
CovidCTNet: an open-source deep learning approach to diagnose covid-19 using small cohort of CT images65
CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV65
Digital health tools for the passive monitoring of depression: a systematic review of methods64
A pragmatic randomized waitlist-controlled effectiveness and cost-effectiveness trial of digital interventions for depression and anxiety64
Deep learning-enabled point-of-care sensing using multiplexed paper-based sensors64
Privacy protections to encourage use of health-relevant digital data in a learning health system63
Estimating the efficacy of symptom-based screening for COVID-1962
Harnessing consumer smartphone and wearable sensors for clinical cancer research62
Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance62
Wearable radio-frequency sensing of respiratory rate, respiratory volume, and heart rate62
Digital health interventions in palliative care: a systematic meta-review61
Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review60
The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field59
Quantifying the use of connected digital products in clinical research58
Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs57
A randomized controlled trial of a smoking cessation smartphone application with a carbon monoxide checker57
Multi-task deep learning for cardiac rhythm detection in wearable devices57
Artificial intelligence for the diagnosis of heart failure56
Cultural adaptation of internet- and mobile-based interventions for mental disorders: a systematic review56
PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging56
COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization56
Automated coronary calcium scoring using deep learning with multicenter external validation55
Privacy-first health research with federated learning55
Enabling precision rehabilitation interventions using wearable sensors and machine learning to track motor recovery54
Deep learning for automated sleep staging using instantaneous heart rate54
Automated screening of sickle cells using a smartphone-based microscope and deep learning54
Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system53
Digital biomarkers: Convergence of digital health technologies and biomarkers53
Accurate diagnosis of lymphoma on whole-slide histopathology images using deep learning53
Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile-health data52
The potential use of digital health technologies in the African context: a systematic review of evidence from Ethiopia52
Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases50
Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state49
Digital phenotyping, behavioral sensing, or personal sensing: names and transparency in the digital age49
Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data49
A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients49
Outcome measures based on digital health technology sensor data: data- and patient-centric approaches49
Machine learning and atherosclerotic cardiovascular disease risk prediction in a multi-ethnic population49
Clinical impact and quality of randomized controlled trials involving interventions evaluating artificial intelligence prediction tools: a systematic review48
Digital advantage in the COVID-19 response: perspective from Canada’s largest integrated digitalized healthcare system48
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography48
Health app policy: international comparison of nine countries’ approaches48
A digital embrace to blunt the curve of COVID19 pandemic47
Modernizing and designing evaluation frameworks for connected sensor technologies in medicine47
Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes47
Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review47
Machine learning for technical skill assessment in surgery: a systematic review46
Sounds of COVID-19: exploring realistic performance of audio-based digital testing46
Aggregating multiple real-world data sources using a patient-centered health-data-sharing platform46
Passive detection of COVID-19 with wearable sensors and explainable machine learning algorithms46
Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care46
Deep transfer learning and data augmentation improve glucose levels prediction in type 2 diabetes patients45
Opportunities and counterintuitive challenges for decentralized clinical trials to broaden participant inclusion45
The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing45
Health digital twins as tools for precision medicine: Considerations for computation, implementation, and regulation44
Machine learning in vascular surgery: a systematic review and critical appraisal44
Integrated multimodal artificial intelligence framework for healthcare applications44
A digital health intervention for cardiovascular disease management in primary care (CONNECT) randomized controlled trial43
Building digital twins of the human immune system: toward a roadmap42
Deep learning in image-based breast and cervical cancer detection: a systematic review and meta-analysis41
Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson’s disease motor symptoms41
WHO Digital Health Guidelines: a milestone for global health41
Health-focused conversational agents in person-centered care: a review of apps41
The diagnostic and triage accuracy of digital and online symptom checker tools: a systematic review41
Development and validation of an interpretable neural network for prediction of postoperative in-hospital mortality41
Digital public health surveillance: a systematic scoping review41
Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors40
Design and testing of a mobile health application rating tool40
Implementation of a multisite, interdisciplinary remote patient monitoring program for ambulatory management of patients with COVID-1939
Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational and genetic studies39
Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients38
Prediction of stress and drug craving ninety minutes in the future with passively collected GPS data38
Evaluation of biases in remote photoplethysmography methods38
Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians38
A digital health industry cohort across the health continuum38
Development and validation of a deep neural network model to predict postoperative mortality, acute kidney injury, and reintubation using a single feature set37
Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes37
The Project Baseline Health Study: a step towards a broader mission to map human health37
Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews37
Assessing the quality of mobile applications in chronic disease management: a scoping review36
Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review35
RETRACTED ARTICLE: Facial expressions can detect Parkinson’s disease: preliminary evidence from videos collected online35
A randomised controlled feasibility trial of E-health application supported care vs usual care after exacerbation of COPD: the RESCUE trial35
Seeing other perspectives: evaluating the use of virtual and augmented reality to simulate visual impairments (OpenVisSim)34
Artificial intelligence sepsis prediction algorithm learns to say “I don’t know”34
Advancing digital health: FDA innovation during COVID-1934
Self-supervised learning for medical image classification: a systematic review and implementation guidelines34
Weak supervision as an efficient approach for automated seizure detection in electroencephalography33
Measuring the effect of Non-Pharmaceutical Interventions (NPIs) on mobility during the COVID-19 pandemic using global mobility data33
Push Button Population Health: The SMART/HL7 FHIR Bulk Data Access Application Programming Interface33
Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening32
Best practices for authors of healthcare-related artificial intelligence manuscripts32
A reimbursement framework for artificial intelligence in healthcare32
Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT32
Can extended reality in the metaverse revolutionise health communication?32
Imputation of missing values for electronic health record laboratory data31
Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials31
Mobile health strategies for blood pressure self-management in urban populations with digital barriers: systematic review and meta-analyses31
Personalized predictions of patient outcomes during and after hospitalization using artificial intelligence31
Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning31
Generation and evaluation of artificial mental health records for Natural Language Processing31
Measurement of respiratory rate using wearable devices and applications to COVID-19 detection31
Low-count whole-body PET with deep learning in a multicenter and externally validated study30
Development and clinical deployment of a smartphone-based visual field deep learning system for glaucoma detection30
Assessing the accuracy of automatic speech recognition for psychotherapy30
Regulatory considerations to keep pace with innovation in digital health products30
Applying speech technologies to assess verbal memory in patients with serious mental illness30
Evaluation of an augmented reality platform for austere surgical telementoring: a randomized controlled crossover study in cricothyroidotomies30
Predicting risk of late age-related macular degeneration using deep learning30
Empowering clinical research in a decentralized world30
Digital approaches to enhancing community engagement in clinical trials30
Smartphone-based digital phenotyping for dry eye toward P4 medicine: a crowdsourced cross-sectional study29
Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study29
Machine-learning-based prediction models for high-need high-cost patients using nationwide clinical and claims data29
Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder29
Computer vision in surgery: from potential to clinical value29
Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition29
Virtual exam for Parkinson’s disease enables frequent and reliable remote measurements of motor function28
Smartphone-based symbol-digit modalities test reliably captures brain damage in multiple sclerosis28
Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review28
Yet Another Automated Gleason Grading System (YAAGGS) by weakly supervised deep learning28
Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches27
Cohort design and natural language processing to reduce bias in electronic health records research27
Deviations from normal bedtimes are associated with short-term increases in resting heart rate27
Medical domain knowledge in domain-agnostic generative AI27
Remote diagnosis of surgical-site infection using a mobile digital intervention: a randomised controlled trial in emergency surgery patients27
The digital scribe in clinical practice: a scoping review and research agenda27
A Delphi consensus statement for digital surgery27
Effectiveness of a digital therapeutic as adjunct to treatment with medication in pediatric ADHD27
Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong26
Belief of having had unconfirmed Covid-19 infection reduces willingness to participate in app-based contact tracing26
Continuous, noninvasive wireless monitoring of flow of cerebrospinal fluid through shunts in patients with hydrocephalus26
Explainable artificial intelligence for mental health through transparency and interpretability for understandability26
Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy26
A data-driven framework for selecting and validating digital health metrics: use-case in neurological sensorimotor impairments26
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