Lancet Digital Health

Papers
(The median citation count of Lancet Digital Health is 8. 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 2022-05-01 to 2026-05-01.)
ArticleCitations
Retraction remedy: a resource for transparent science631
Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models470
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis456
Correction to Lancet Digit Health 2023; 5: e446–57426
Correction to Lancet Digit Health 2024; 6: e791–802396
Machine learning to predict type 1 diabetes in children385
ChatGPT: the future of discharge summaries?350
Generative Pre-trained Transformer 4 (GPT-4) in clinical settings288
Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world248
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study236
In the era of digitalisation and biosignatures, is C-reactive protein still the one to beat?231
Targeting respiratory syncytial virus vaccination using individual prediction223
Challenges for augmenting intelligence in cardiac imaging220
Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies212
A deep-learning-enabled diagnosis of ovarian cancer – Authors' reply202
Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study201
Accelerating action for gender equality in health198
Balancing AI innovation with patient safety197
Technology for world elimination of neglected tropical diseases195
Health insights from face photographs155
Harnessing population-wide health data to predict cancer risk153
Fairly evaluating the performance of normative models150
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 stud149
Digital health funding for COVID-19 vaccine deployment across four major donor agencies143
Large language model integration in Philippine ophthalmology: early challenges and steps forward141
AI-CAD for tuberculosis and other global high-burden diseases137
Accurate classification of pulmonary nodules by a combined model of clinical, imaging, and cell-free DNA methylation biomarkers: a model development and external validation study133
Drone delivery of automated external defibrillators compared with ambulance arrival in real-life suspected out-of-hospital cardiac arrests: a prospective observational study in Sweden126
Bridging the gap: aligning clinical decision support regulation with clinical practice in the era of artificial intelligence123
A future role for health applications of large language models depends on regulators enforcing safety standards118
Efficacy of standalone smartphone apps for mental health: an updated systematic review and meta-analysis113
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study112
Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis112
Trust, not technology: governing access to health data as the decisive challenge for the UK112
Decolonising health data106
Synthetic data, synthetic trust: navigating data challenges in the digital revolution104
Using artificial intelligence to switch from accident to sagacity in the serendipitous detection of uncommon diseases102
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study99
Effect of digital psychoeducation and peer support on the mental health of family carers supporting individuals with psychosis in England (COPe-support): a randomised clinical trial98
A long STANDING commitment to improving health care96
Thank you to The Lancet Digital Health's statistical and peer reviewers in 202291
Can electronic medical records predict neonatal seizures?91
Safe care from home for complicated pregnancies?86
US COVID-19 clinical trial leadership gender disparities85
The MAIDA initiative: establishing a framework for global medical-imaging data sharing84
A practical framework for operationalising responsible and equitable artificial intelligence in health care: tackling bias, inequity, and implementation challenges83
Radiomics in neuro-oncological clinical trials83
An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation83
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility82
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 intel80
Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study78
Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study76
Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study73
A response to evaluating national data flows72
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations72
Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis71
Overlooked and under-reported: the impact of cyberattacks on primary care in the UK National Health Service70
Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: a population-based machine-learning study69
Moving forward with machine learning models in acute chest pain69
A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan68
Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study68
RareArena: a comprehensive benchmark dataset unveiling the potential of large language models in rare disease diagnosis68
AI-enabled forecasting of prehospital transfusion needs in patients with trauma: a multinational, registry-based, retrospective, machine learning development and validation study68
Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis67
Performance of universal and stratified computer-aided detection thresholds for chest x-ray-based tuberculosis screening: a cross-sectional, diagnostic accuracy study67
Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study65
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in England65
Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with hypertension: a systematic review and meta-analysis of randomised controlled trials64
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 Biobank64
Efficacy of telemedicine for the management of cardiovascular disease: a systematic review and meta-analysis63
Is predicting metastatic phaeochromocytoma and paraganglioma still effective without methoxytyramine? – Authors' reply62
Correction to Lancet Digit Health 2024; 6: e562–6962
Correction to Lancet Digit Health 2022; 4: e497–50662
A machine learning-based screening tool for genetic syndromes in children – Authors' reply61
5 years of The Lancet Digital Health60
AI for medical diagnosis: does a single negative trial mean it is ineffective?60
Reappraising screening metrics and methodological considerations in artificial intelligence-augmented mammography59
Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study59
Machine learning COVID-19 detection from wearables58
Personalised electronic health programme for recovery after major abdominal surgery: a multicentre, single-blind, randomised, placebo-controlled trial58
Value of artificial intelligence in neuro-oncology57
Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study56
Assessing genotype−phenotype correlations in colorectal cancer with deep learning: a multicentre cohort study56
Effects of the COVID-19 pandemic on antibiotic use and resistance in French hospitals, 2019–22: a retrospective ecological analysis of national surveillance data56
The promise of a model-based psychiatry: building computational models of mental ill health54
Associations between contralesional neuroplasticity and motor impairment through deep learning-derived MRI regional brain age in chronic stroke (ENIGMA): a multicohort, retrospective, observational st54
From text to treatment: the crucial role of validation for generative large language models in health care53
Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation52
Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing52
Digital twins, synthetic patient data, and in-silico trials: can they empower paediatric clinical trials?51
Standardising the role of a digital navigator in behavioural health: a systematic review51
Attitudes and perceptions of medical researchers towards the use of artificial intelligence chatbots in the scientific process: an international cross-sectional survey50
Predicting seizure recurrence from medical records using large language models50
Digital therapy for depression in multiple sclerosis50
Correction to Lancet Digit Health 2024; published online Sept 17. https://doi.org/10.1016/S2589-7500(24)00143-249
Digital transformation of ovarian cancer diagnosis and care49
Just in time: detecting cardiac arrest with smartwatch technology48
Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study47
When to and when not to use machine learning in risk prediction models47
Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review47
Correction to Lancet Digital Health 2025; 7: 10088247
Snapshot artificial intelligence—determination of ejection fraction from a single frame still image: a multi-institutional, retrospective model development and validation study45
Ethical and regulatory challenges of large language models in medicine44
The Jevons Paradox in global health: efficiency, demand, and the AI dilemma44
Generating scholarly content with ChatGPT: ethical challenges for medical publishing44
Digital health equity for older populations44
Wearable technology and the cardiovascular system: the future of patient assessment44
Data solidarity: a blueprint for governing health futures44
Challenges of AI-based pulmonary function estimation from chest x-rays42
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, Canada41
Improving digital study designs: better metrics, systematic reporting, and an engineering mindset41
Menstrual irregularities and vaginal bleeding after COVID-19 vaccination reported to v-safe active surveillance, USA in December, 2020–January, 2022: an observational cohort study41
AI models in health care are not colour blind and we should not be either41
The importance of microbiology reference laboratories and adequate funding for infectious disease surveillance40
Harnessing wearables and mobile phones to improve glycemic outcomes with automated insulin delivery40
Automated external defibrillator drones and their role in emergency response40
AI for identification of systemic biomarkers from external eye photos: a promising field in the oculomics revolution40
Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction model40
Artificial intelligence in medicine and the pursuit of environmentally responsible science39
Label-efficient computational tumour infiltrating lymphocyte assessment in breast cancer (ECTIL): multicentre validation in 2340 patients with breast cancer39
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 hospitals37
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility37
Can large language models help young researchers develop new clinical research ideas?37
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 trial37
Utilising the Benefit Risk Assessment of Vaccines (BRAVE) toolkit to evaluate the benefits and risks of Vaxzevria in the EU: a population-based study36
The potential for large language models to transform cardiovascular medicine36
Reflecting on lived experience expertise in digital mental health research36
A prospectively deployed deep learning-enabled automated quality assurance tool for oncological palliative spine radiation therapy35
Effect of epileptic activity on outcome for critically ill patients35
Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the FLARE22 challenge35
Curbing the carbon footprint of health care35
Wearable health data privacy35
Artificial intelligence-driven cardiac amyloidosis screening35
Importance of sample size on the quality and utility of AI-based prediction models for healthcare35
Twitter, public health, and misinformation34
Feedback loops in intensive care unit prognostic models: an under-recognised threat to clinical validity34
The architectural gap in clinical artificial intelligence34
Deep learning with weak annotation from diagnosis reports for detection of multiple head disorders: a prospective, multicentre study33
Paediatric safety assessment of BNT162b2 vaccination in a multistate hospital-based electronic health record system in the USA: a retrospective analysis33
Stepping stones and challenges in the use of artificial intelligence in the diagnosis of echinococcosis33
Overcoming colonialism in pathogen genomics32
Artificial intelligence-guided point-of-care ultrasonography for cardiomyopathy detection32
Correction to Lancet Digit Health 2023; 5: e404–2032
Thank you to The Lancet Digital Health statistical and peer reviewers in 202531
Migration background, skin colour, gender, and infectious disease presentation in clinical vignettes31
Independent and openly reported head-to-head comparative validation studies of AI medical devices: a necessary step towards safe and responsible clinical AI deployment31
Artificial intelligence for post-treatment prediction in age-related macular degeneration31
Smartwatch-derived versus self-reported outcomes of physiological recovery after COVID-19, influenza, and group A streptococcus: a 2-year prospective cohort study31
Combating medical misinformation and rebuilding trust in the USA31
Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies30
Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening30
Early qualitative and quantitative amplitude-integrated electroencephalogram and raw electroencephalogram for predicting long-term neurodevelopmental outcomes in extremely preterm infants in the Nethe30
The global Dx AMR collaborative: an approach to strengthen the role of diagnostics in combating antimicrobial resistance29
How can artificial intelligence transform the training of medical students and physicians?29
CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research29
Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study29
Leveraging artificial intelligence for predicting spontaneous closure of perimembranous ventricular septal defect in children: a multicentre, retrospective study in China29
Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study28
Implementation of an automated deep learning-based quality assurance tool for vertebral body identification in radiotherapy planning28
Augmenting digital twins with federated learning in medicine28
Fairly evaluating the performance of normative models – Authors' reply28
Online video versus face-to-face preoperative consultation for major abdominal surgery (VIDEOGO): a multicentre, open-label, randomised, controlled, non-inferiority trial27
Re-engineering a machine learning phenotype to adapt to the changing COVID-19 landscape: a machine learning modelling study from the N3C and RECOVER consortia26
Artificial intelligence and tumour-infiltrating lymphocytes in breast cancer: bridging innovation and feasibility towards clinical utility26
Multiomics single timepoint measurements to predict severe COVID-19 – Authors' reply26
Taking responsibility for child safety online26
Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study25
Strategies for integrating artificial intelligence into mammography screening programmes: a retrospective simulation analysis25
Validation of the myocardial-ischaemic-injury-index machine learning algorithm to guide the diagnosis of myocardial infarction in a heterogenous population: a prespecified exploratory analysis25
Effect of COVID-19 vaccination and booster on maternal–fetal outcomes: a retrospective cohort study25
An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation24
Pathology in the era of generative AI24
Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study24
Crossing the frontier: the first global AI safety summit24
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
Comparison of eight prehospital early warning scores in life-threatening acute respiratory distress: a prospective, observational, multicentre, ambulance-based, external validation study23
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 trial23
Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review22
Bihormonal fully closed-loop system for the treatment of type 1 diabetes: a real-world multicentre, prospective, single-arm trial in the Netherlands22
Effect of telehealth-integrated antenatal care on pregnancy outcomes in Australia: an interrupted time-series analysis22
Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study22
The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study22
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
Artificial intelligence for tumour tissue detection and histological regression grading in oesophageal adenocarcinomas: a retrospective algorithm development and validation study21
Mitigating the risk of artificial intelligence bias in cardiovascular care21
Human mobility patterns in Brazil to inform sampling sites for early pathogen detection and routes of spread: a network modelling and validation study21
Predicting peritoneal recurrence by artificial intelligence21
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-1921
Thank you to The Lancet Digital Health's statistical and peer reviewers in 202421
Leveraging digital technologies to reduce cancer disparities in low-income and middle-income countries20
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
Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis20
Decentralised clinical trials: ethical opportunities and challenges20
Utilising routinely collected clinical data through time series deep learning to improve identification of bacterial bloodstream infections: a retrospective cohort study20
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
Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study19
Beyond artificial intelligence psychosis: a functional typology of large language model-associated psychotic phenomena19
The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review19
Therapist-guided internet-based psychodynamic therapy versus cognitive behavioural therapy for adolescent depression in Sweden: a randomised, clinical, non-inferiority trial19
Does deidentification of data from wearable devices give us a false sense of security? A systematic review19
A deep-learning-enabled diagnosis of ovarian cancer19
Vaccines for pregnant people: are we missing the forest for the trees?19
Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study18
Expanding people-centred primary health care with digital adaptation kits for self-care interventions18
End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study18
Using ChatGPT to write patient clinic letters17
Preserving the integrity of clinical trials17
Clinical ground truth in machine learning for early sepsis diagnosis17
Medical artificial intelligence for clinicians: the lost cognitive perspective17
Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study17
Passive sensing at scale to transform understanding of poor mental health17
Agentic artificial intelligence in eye care: is clinical autonomy finally within reach?17
Highly sensitive detection platform-based diagnosis of oesophageal squamous cell carcinoma in China: a multicentre, case–control, diagnostic study17
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 studies17
Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist16
Transforming women's health, empowerment, and gender equality with digital health: evidence-based policy and practice16
The effect of using a large language model to respond to patient messages16
Proteomic prediction of diverse incident diseases: a machine learning-guided biomarker discovery study using data from a prospective cohort study16
Expanding electrocardiogram abilities for postoperative mortality prediction with deep learning15
Clinical trials for implantable neural prostheses: understanding the ethical and technical requirements15
Computer-aided reading of chest radiographs for paediatric tuberculosis: current status and future directions15
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 study15
Correction to Lancet Digit Health 2022; 4: e256–6515
Correction to Lancet Digit Health 2025; 7: e161–6615
AI for mammography: making double screen-reading history15
Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study14
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 France14
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 Consortium14
The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study14
The next generation of evidence synthesis for diagnostic accuracy studies in artificial intelligence14
Challenges of AI-based pulmonary function estimation from chest x-rays – Authors' reply13
AI recognition of patient race in medical imaging: a modelling study13
Digital prehabilitation—a solution to resource shortages?13
The impact of commercial health datasets on medical research and health-care algorithms13
Paradox of telemedicine: building or neglecting trust and equity13
Treating type 2 diabetes: moving towards precision medicine13
Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study13
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 surveys13
Pan-mediastinal neoplasm diagnosis via nationwide federated learning: a multicentre cohort study13
From the 100 Day Mission to 100 lines of software development: how to improve early outbreak analytics12
Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study12
Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance12
Data capture and sharing in the COVID-19 pandemic: a cause for concern12
Identification of drug repurposing candidates for amyotrophic lateral sclerosis using electronic health records: a retrospective cohort study12
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-analysis12
Identifying adverse childhood experiences with electronic health records of linked mothers and children in England: a multistage development and validation study12
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 study12
Ischaemic stroke recurrence in patients with symptomatic intracranial atherosclerotic stenosis in China (PROMISE): a multivariable prediction model development and validation study11
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