Lancet Digital Health

Papers
(The median citation count of Lancet Digital Health is 7. 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 2022-06-01 to 2026-06-01.)
ArticleCitations
Retraction remedy: a resource for transparent science635
In the era of digitalisation and biosignatures, is C-reactive protein still the one to beat?475
Correction to Lancet Digit Health 2023; 5: e446–57474
Correction to Lancet Digit Health 2024; 6: e791–802443
Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies406
Accelerating action for gender equality in health397
Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world354
Machine learning to predict type 1 diabetes in children296
Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models255
Generative Pre-trained Transformer 4 (GPT-4) in clinical settings255
Balancing AI innovation with patient safety254
Technology for world elimination of neglected tropical diseases225
Targeting respiratory syncytial virus vaccination using individual prediction223
Challenges for augmenting intelligence in cardiac imaging219
A deep-learning-enabled diagnosis of ovarian cancer – Authors' reply215
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis204
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study201
Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study197
ChatGPT: the future of discharge summaries?158
Health insights from face photographs153
Harnessing population-wide health data to predict cancer risk150
Efficacy of standalone smartphone apps for mental health: an updated systematic review and meta-analysis146
Fairly evaluating the performance of normative models143
Synthetic data, synthetic trust: navigating data challenges in the digital revolution138
Large language model integration in Philippine ophthalmology: early challenges and steps forward133
Digital health funding for COVID-19 vaccine deployment across four major donor agencies125
Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis123
A future role for health applications of large language models depends on regulators enforcing safety standards119
Decolonising health data118
A multi-platform approach to identify a blood-based host protein signature for distinguishing between bacterial and viral infections in febrile children (PERFORM): a multi-cohort machine learning stud117
Bridging the gap: aligning clinical decision support regulation with clinical practice in the era of artificial intelligence116
Drone delivery of automated external defibrillators compared with ambulance arrival in real-life suspected out-of-hospital cardiac arrests: a prospective observational study in Sweden115
Accurate classification of pulmonary nodules by a combined model of clinical, imaging, and cell-free DNA methylation biomarkers: a model development and external validation study107
Trust, not technology: governing access to health data as the decisive challenge for the UK101
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study101
Thank you to The Lancet Digital Health's statistical and peer reviewers in 2022100
AI-CAD for tuberculosis and other global high-burden diseases100
Safe care from home for complicated pregnancies?96
US COVID-19 clinical trial leadership gender disparities94
Adolescent obesity in the digital age: navigating risks and opportunities89
The MAIDA initiative: establishing a framework for global medical-imaging data sharing87
Using artificial intelligence to switch from accident to sagacity in the serendipitous detection of uncommon diseases86
Can electronic medical records predict neonatal seizures?85
A long STANDING commitment to improving health care85
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study84
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility83
Virtual reality-based cognitive remediation versus virtual reality control in people with mood or psychosis spectrum disorders in Denmark: a single-centre, double-blind, randomised controlled trial80
Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study74
Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intel73
Radiomics in neuro-oncological clinical trials73
A practical framework for operationalising responsible and equitable artificial intelligence in health care: tackling bias, inequity, and implementation challenges72
Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study72
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations71
Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study71
An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation71
RareArena: a comprehensive benchmark dataset unveiling the potential of large language models in rare disease diagnosis70
A response to evaluating national data flows70
Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis70
Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study69
Overlooked and under-reported: the impact of cyberattacks on primary care in the UK National Health Service69
AI-enabled forecasting of prehospital transfusion needs in patients with trauma: a multinational, registry-based, retrospective, machine learning development and validation study68
Navigating the promise and pitfalls of dashboards in health policy decision making: experiences from Ghana, India, and South Africa67
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in England66
Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank65
Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with hypertension: a systematic review and meta-analysis of randomised controlled trials64
Co-intelligence: a proposal for human–artificial intelligence collaboration for large language models in medical research64
Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study63
Efficacy of telemedicine for the management of cardiovascular disease: a systematic review and meta-analysis62
Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis62
Performance of universal and stratified computer-aided detection thresholds for chest x-ray-based tuberculosis screening: a cross-sectional, diagnostic accuracy study62
A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan62
AI for medical diagnosis: does a single negative trial mean it is ineffective?60
Correction to Lancet Digit Health 2022; 4: e497–50659
Correction to Lancet Digit Health 2024; 6: e562–6957
5 years of The Lancet Digital Health56
Reappraising screening metrics and methodological considerations in artificial intelligence-augmented mammography56
Is predicting metastatic phaeochromocytoma and paraganglioma still effective without methoxytyramine? – Authors' reply56
Machine learning COVID-19 detection from wearables55
Standardising the role of a digital navigator in behavioural health: a systematic review55
Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study55
Personalised electronic health programme for recovery after major abdominal surgery: a multicentre, single-blind, randomised, placebo-controlled trial54
Effects of the COVID-19 pandemic on antibiotic use and resistance in French hospitals, 2019–22: a retrospective ecological analysis of national surveillance data54
Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing54
Associations between contralesional neuroplasticity and motor impairment through deep learning-derived MRI regional brain age in chronic stroke (ENIGMA): a multicohort, retrospective, observational st53
Assessing genotype−phenotype correlations in colorectal cancer with deep learning: a multicentre cohort study52
Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study52
Value of artificial intelligence in neuro-oncology51
Digital twins, synthetic patient data, and in-silico trials: can they empower paediatric clinical trials?51
The promise of a model-based psychiatry: building computational models of mental ill health51
Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation51
Attitudes and perceptions of medical researchers towards the use of artificial intelligence chatbots in the scientific process: an international cross-sectional survey50
Just in time: detecting cardiac arrest with smartwatch technology49
Correction to Lancet Digit Health 2024; published online Sept 17. https://doi.org/10.1016/S2589-7500(24)00143-249
Predicting seizure recurrence from medical records using large language models49
From text to treatment: the crucial role of validation for generative large language models in health care49
When to and when not to use machine learning in risk prediction models48
Digital therapy for depression in multiple sclerosis48
Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study46
Correction to Lancet Digital Health 2025; 7: 10088246
Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review46
Generating scholarly content with ChatGPT: ethical challenges for medical publishing45
Data solidarity: a blueprint for governing health futures45
Snapshot artificial intelligence—determination of ejection fraction from a single frame still image: a multi-institutional, retrospective model development and validation study44
The Jevons Paradox in global health: efficiency, demand, and the AI dilemma43
Digital transformation of ovarian cancer diagnosis and care43
Wearable technology and the cardiovascular system: the future of patient assessment43
Digital health equity for older populations42
Improving digital study designs: better metrics, systematic reporting, and an engineering mindset42
Ethical and regulatory challenges of large language models in medicine42
Challenges of AI-based pulmonary function estimation from chest x-rays42
Harnessing wearables and mobile phones to improve glycemic outcomes with automated insulin delivery41
Automated external defibrillator drones and their role in emergency response41
Simple meal announcements and pramlintide delivery versus carbohydrate counting in type 1 diabetes with automated fast-acting insulin aspart delivery: a randomised crossover trial in Montreal, Canada40
The importance of microbiology reference laboratories and adequate funding for infectious disease surveillance40
AI for identification of systemic biomarkers from external eye photos: a promising field in the oculomics revolution40
Feasibility of wearable sensor signals and self-reported symptoms to prompt at-home testing for acute respiratory viruses in the USA (DETECT-AHEAD): a decentralised, randomised controlled trial39
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility37
Artificial intelligence in medicine and the pursuit of environmentally responsible science37
Utilising the Benefit Risk Assessment of Vaccines (BRAVE) toolkit to evaluate the benefits and risks of Vaxzevria in the EU: a population-based study37
Label-efficient computational tumour infiltrating lymphocyte assessment in breast cancer (ECTIL): multicentre validation in 2340 patients with breast cancer37
Curbing the carbon footprint of health care36
A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals36
Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction model36
Menstrual irregularities and vaginal bleeding after COVID-19 vaccination reported to v-safe active surveillance, USA in December, 2020–January, 2022: an observational cohort study36
AI models in health care are not colour blind and we should not be either36
Can large language models help young researchers develop new clinical research ideas?36
The potential for large language models to transform cardiovascular medicine36
Importance of sample size on the quality and utility of AI-based prediction models for healthcare36
Reflecting on lived experience expertise in digital mental health research35
Deep learning with weak annotation from diagnosis reports for detection of multiple head disorders: a prospective, multicentre study35
Artificial intelligence-driven cardiac amyloidosis screening35
Twitter, public health, and misinformation35
Effect of epileptic activity on outcome for critically ill patients34
The architectural gap in clinical artificial intelligence34
Wearable health data privacy33
An online singing-based breathing and wellbeing programme (ENO Breathe) in people with long COVID breathlessness in the UK: a cohort study33
Feedback loops in intensive care unit prognostic models: an under-recognised threat to clinical validity33
A prospectively deployed deep learning-enabled automated quality assurance tool for oncological palliative spine radiation therapy33
Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the FLARE22 challenge33
Artificial intelligence-guided point-of-care ultrasonography for cardiomyopathy detection32
Correction to Lancet Digit Health 2023; 5: e404–2032
CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research32
Paediatric safety assessment of BNT162b2 vaccination in a multistate hospital-based electronic health record system in the USA: a retrospective analysis32
Artificial intelligence for post-treatment prediction in age-related macular degeneration32
Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies32
Overcoming colonialism in pathogen genomics31
Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study31
Stepping stones and challenges in the use of artificial intelligence in the diagnosis of echinococcosis30
Early qualitative and quantitative amplitude-integrated electroencephalogram and raw electroencephalogram for predicting long-term neurodevelopmental outcomes in extremely preterm infants in the Nethe30
How can artificial intelligence transform the training of medical students and physicians?30
Independent and openly reported head-to-head comparative validation studies of AI medical devices: a necessary step towards safe and responsible clinical AI deployment30
Thank you to The Lancet Digital Health statistical and peer reviewers in 202529
Smartwatch-derived versus self-reported outcomes of physiological recovery after COVID-19, influenza, and group A streptococcus: a 2-year prospective cohort study29
Migration background, skin colour, gender, and infectious disease presentation in clinical vignettes28
The global Dx AMR collaborative: an approach to strengthen the role of diagnostics in combating antimicrobial resistance28
Leveraging artificial intelligence for predicting spontaneous closure of perimembranous ventricular septal defect in children: a multicentre, retrospective study in China27
Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening27
Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study27
Combating medical misinformation and rebuilding trust in the USA27
Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial26
Augmenting digital twins with federated learning in medicine26
Implementation of an automated deep learning-based quality assurance tool for vertebral body identification in radiotherapy planning25
Crossing the frontier: the first global AI safety summit25
Pathology in the era of generative AI25
Artificial intelligence and tumour-infiltrating lymphocytes in breast cancer: bridging innovation and feasibility towards clinical utility25
Taking responsibility for child safety online24
Effect of COVID-19 vaccination and booster on maternal–fetal outcomes: a retrospective cohort study24
An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation24
Multiomics single timepoint measurements to predict severe COVID-19 – Authors' reply24
Strategies for integrating artificial intelligence into mammography screening programmes: a retrospective simulation analysis24
Online video versus face-to-face preoperative consultation for major abdominal surgery (VIDEOGO): a multicentre, open-label, randomised, controlled, non-inferiority trial24
Re-engineering a machine learning phenotype to adapt to the changing COVID-19 landscape: a machine learning modelling study from the N3C and RECOVER consortia24
Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study24
Fairly evaluating the performance of normative models – Authors' reply24
Emotional competence self-help app versus cognitive behavioural self-help app versus self-monitoring app to prevent depression in young adults with elevated risk (ECoWeB PREVENT): an international, mu23
Bihormonal fully closed-loop system for the treatment of type 1 diabetes: a real-world multicentre, prospective, single-arm trial in the Netherlands23
Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study23
Advances in decision support for diagnosis and early management of acute leukaemia22
Artificial intelligence-assisted detection of nasopharyngeal carcinoma on endoscopic images: a national, multicentre, model development and validation study22
Predicting hospitalisation for heart failure and death in patients with, or at risk of, heart failure before first hospitalisation: a retrospective model development and external validation study22
Human mobility patterns in Brazil to inform sampling sites for early pathogen detection and routes of spread: a network modelling and validation study22
Comparison of eight prehospital early warning scores in life-threatening acute respiratory distress: a prospective, observational, multicentre, ambulance-based, external validation study22
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-1922
Mitigating the risk of artificial intelligence bias in cardiovascular care21
Artificial intelligence for tumour tissue detection and histological regression grading in oesophageal adenocarcinomas: a retrospective algorithm development and validation study21
Effect of telehealth-integrated antenatal care on pregnancy outcomes in Australia: an interrupted time-series analysis21
Artificial intelligence analysis of temporalis muscle thickness for monitoring sarcopenia and clinical outcomes in individuals with paediatric brain tumours: a retrospective cohort study21
Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review21
Thank you to The Lancet Digital Health's statistical and peer reviewers in 202420
Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis20
The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study20
Decentralised clinical trials: ethical opportunities and challenges20
Digital adherence technology interventions to reduce poor end-of-treatment outcomes and recurrence among adults with drug-sensitive tuberculosis in Ethiopia: a three-arm, pragmatic, cluster-randomised20
Utilising routinely collected clinical data through time series deep learning to improve identification of bacterial bloodstream infections: a retrospective cohort study20
Profiling post-COVID-19 condition across different variants of SARS-CoV-2: a prospective longitudinal study in unvaccinated wild-type, unvaccinated alpha-variant, and vaccinated delta-variant populati20
Does deidentification of data from wearable devices give us a false sense of security? A systematic review19
End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study19
Leveraging digital technologies to reduce cancer disparities in low-income and middle-income countries19
Therapist-guided internet-based psychodynamic therapy versus cognitive behavioural therapy for adolescent depression in Sweden: a randomised, clinical, non-inferiority trial19
Beyond artificial intelligence psychosis: a functional typology of large language model-associated psychotic phenomena19
Effects of large language model-generated, patient-oriented discharge summaries on patient activation: a single-centre, single-blind, randomised controlled trial in Germany19
Vaccines for pregnant people: are we missing the forest for the trees?19
Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study18
Passive sensing at scale to transform understanding of poor mental health18
A deep-learning-enabled diagnosis of ovarian cancer18
Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study18
Clinical ground truth in machine learning for early sepsis diagnosis17
The effect of using a large language model to respond to patient messages17
Expanding people-centred primary health care with digital adaptation kits for self-care interventions17
Transforming women's health, empowerment, and gender equality with digital health: evidence-based policy and practice17
Highly sensitive detection platform-based diagnosis of oesophageal squamous cell carcinoma in China: a multicentre, case–control, diagnostic study17
Agentic artificial intelligence in eye care: is clinical autonomy finally within reach?17
Proteomic prediction of diverse incident diseases: a machine learning-guided biomarker discovery study using data from a prospective cohort study17
Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study16
Identification of key factors related to digital health observational study adherence and retention by data-driven approaches: an exploratory secondary analysis of two prospective longitudinal studies16
Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist16
Preserving the integrity of clinical trials16
Using ChatGPT to write patient clinic letters16
Correction to Lancet Digit Health 2025; 7: e161–6615
Expanding electrocardiogram abilities for postoperative mortality prediction with deep learning15
The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study15
AI for mammography: making double screen-reading history15
Evaluation of a machine-learning model based on laboratory parameters for the prediction of acute leukaemia subtypes: a multicentre model development and validation study in France15
Medical artificial intelligence for clinicians: the lost cognitive perspective15
Trends in invasive bacterial diseases during the first 2 years of the COVID-19 pandemic: analyses of prospective surveillance data from 30 countries and territories in the IRIS Consortium15
Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study14
Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study14
The next generation of evidence synthesis for diagnostic accuracy studies in artificial intelligence14
Clinical trials for implantable neural prostheses: understanding the ethical and technical requirements14
Computer-aided reading of chest radiographs for paediatric tuberculosis: current status and future directions14
Challenges of AI-based pulmonary function estimation from chest x-rays – Authors' reply13
AI recognition of patient race in medical imaging: a modelling study13
Diagnostic accuracy of a machine learning algorithm using point-of-care high-sensitivity cardiac troponin I for rapid rule-out of myocardial infarction: a retrospective study13
Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study13
Treating type 2 diabetes: moving towards precision medicine13
The impact of commercial health datasets on medical research and health-care algorithms13
Identification of drug repurposing candidates for amyotrophic lateral sclerosis using electronic health records: a retrospective cohort study12
Data capture and sharing in the COVID-19 pandemic: a cause for concern12
Paradox of telemedicine: building or neglecting trust and equity12
Identifying adverse childhood experiences with electronic health records of linked mothers and children in England: a multistage development and validation study12
COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys12
Pan-mediastinal neoplasm diagnosis via nationwide federated learning: a multicentre cohort study12
From the 100 Day Mission to 100 lines of software development: how to improve early outbreak analytics12
Digital prehabilitation—a solution to resource shortages?12
Equitable precision medicine for type 2 diabetes11
The global effect of digital health technologies on health workers’ competencies and health workplace: an umbrella review of systematic reviews and lexical-based and sentence-based meta-analysis11
Enhancing the success of IVF with artificial intelligence11
Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study11
Opportunities for opioid overdose prediction: building a population health approach11
Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance11
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