OOIR: Observatory of International Research

Papers

(The TQCC of Lancet Digital Health is 33. 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.)

Article	Citations
Retraction remedy: a resource for transparent science	631
Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models	470
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis	456
Correction to Lancet Digit Health 2023; 5: e446–57	426
Correction to Lancet Digit Health 2024; 6: e791–802	396
Machine learning to predict type 1 diabetes in children	385
ChatGPT: the future of discharge summaries?	350
Generative Pre-trained Transformer 4 (GPT-4) in clinical settings	288
Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world	248
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study	236
In the era of digitalisation and biosignatures, is C-reactive protein still the one to beat?	231
Targeting respiratory syncytial virus vaccination using individual prediction	223
Challenges for augmenting intelligence in cardiac imaging	220
Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies	212
A deep-learning-enabled diagnosis of ovarian cancer – Authors' reply	202
Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study	201
Accelerating action for gender equality in health	198
Balancing AI innovation with patient safety	197
Technology for world elimination of neglected tropical diseases	195
Health insights from face photographs	155
Harnessing population-wide health data to predict cancer risk	153
Fairly evaluating the performance of normative models	150
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 stud	149
Digital health funding for COVID-19 vaccine deployment across four major donor agencies	143
Large language model integration in Philippine ophthalmology: early challenges and steps forward	141

AI-CAD for tuberculosis and other global high-burden diseases	137
Accurate classification of pulmonary nodules by a combined model of clinical, imaging, and cell-free DNA methylation biomarkers: a model development and external validation study	133
Drone delivery of automated external defibrillators compared with ambulance arrival in real-life suspected out-of-hospital cardiac arrests: a prospective observational study in Sweden	126
Bridging the gap: aligning clinical decision support regulation with clinical practice in the era of artificial intelligence	123
A future role for health applications of large language models depends on regulators enforcing safety standards	118
Efficacy of standalone smartphone apps for mental health: an updated systematic review and meta-analysis	113
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study	112
Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis	112
Trust, not technology: governing access to health data as the decisive challenge for the UK	112
Decolonising health data	106
Synthetic data, synthetic trust: navigating data challenges in the digital revolution	104
Using artificial intelligence to switch from accident to sagacity in the serendipitous detection of uncommon diseases	102
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study	99
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 trial	98
A long STANDING commitment to improving health care	96
Thank you to The Lancet Digital Health's statistical and peer reviewers in 2022	91
Can electronic medical records predict neonatal seizures?	91
Safe care from home for complicated pregnancies?	86
US COVID-19 clinical trial leadership gender disparities	85
The MAIDA initiative: establishing a framework for global medical-imaging data sharing	84
Radiomics in neuro-oncological clinical trials	83
An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation	83
A practical framework for operationalising responsible and equitable artificial intelligence in health care: tackling bias, inequity, and implementation challenges	83
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility	82
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 intel	80
Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study	78
Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study	76
Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study	73
A response to evaluating national data flows	72
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations	72
Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis	71
Overlooked and under-reported: the impact of cyberattacks on primary care in the UK National Health Service	70
Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: a population-based machine-learning study	69
Moving forward with machine learning models in acute chest pain	69
A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan	68
Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study	68
RareArena: a comprehensive benchmark dataset unveiling the potential of large language models in rare disease diagnosis	68
AI-enabled forecasting of prehospital transfusion needs in patients with trauma: a multinational, registry-based, retrospective, machine learning development and validation study	68
Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis	67
Performance of universal and stratified computer-aided detection thresholds for chest x-ray-based tuberculosis screening: a cross-sectional, diagnostic accuracy study	67
Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study	65
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in England	65
Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with hypertension: a systematic review and meta-analysis of randomised controlled trials	64
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 Biobank	64
Efficacy of telemedicine for the management of cardiovascular disease: a systematic review and meta-analysis	63
Is predicting metastatic phaeochromocytoma and paraganglioma still effective without methoxytyramine? – Authors' reply	62
Correction to Lancet Digit Health 2024; 6: e562–69	62
Correction to Lancet Digit Health 2022; 4: e497–506	62
A machine learning-based screening tool for genetic syndromes in children – Authors' reply	61
5 years of The Lancet Digital Health	60

AI for medical diagnosis: does a single negative trial mean it is ineffective?	60
Reappraising screening metrics and methodological considerations in artificial intelligence-augmented mammography	59
Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study	59
Personalised electronic health programme for recovery after major abdominal surgery: a multicentre, single-blind, randomised, placebo-controlled trial	58
Machine learning COVID-19 detection from wearables	58
Value of artificial intelligence in neuro-oncology	57
Assessing genotype−phenotype correlations in colorectal cancer with deep learning: a multicentre cohort study	56
Effects of the COVID-19 pandemic on antibiotic use and resistance in French hospitals, 2019–22: a retrospective ecological analysis of national surveillance data	56
Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study	56
The promise of a model-based psychiatry: building computational models of mental ill health	54
Associations between contralesional neuroplasticity and motor impairment through deep learning-derived MRI regional brain age in chronic stroke (ENIGMA): a multicohort, retrospective, observational st	54
From text to treatment: the crucial role of validation for generative large language models in health care	53
Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation	52
Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing	52
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 review	51
Attitudes and perceptions of medical researchers towards the use of artificial intelligence chatbots in the scientific process: an international cross-sectional survey	50
Predicting seizure recurrence from medical records using large language models	50
Digital therapy for depression in multiple sclerosis	50
Correction to Lancet Digit Health 2024; published online Sept 17. https://doi.org/10.1016/S2589-7500(24)00143-2	49
Digital transformation of ovarian cancer diagnosis and care	49
Just in time: detecting cardiac arrest with smartwatch technology	48
Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study	47
When to and when not to use machine learning in risk prediction models	47
Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review	47
Correction to Lancet Digital Health 2025; 7: 100882	47
Snapshot artificial intelligence—determination of ejection fraction from a single frame still image: a multi-institutional, retrospective model development and validation study	45
Ethical and regulatory challenges of large language models in medicine	44
The Jevons Paradox in global health: efficiency, demand, and the AI dilemma	44
Generating scholarly content with ChatGPT: ethical challenges for medical publishing	44
Digital health equity for older populations	44
Wearable technology and the cardiovascular system: the future of patient assessment	44
Data solidarity: a blueprint for governing health futures	44
Challenges of AI-based pulmonary function estimation from chest x-rays	42
Menstrual irregularities and vaginal bleeding after COVID-19 vaccination reported to v-safe active surveillance, USA in December, 2020–January, 2022: an observational cohort study	41
AI models in health care are not colour blind and we should not be either	41
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, Canada	41
Improving digital study designs: better metrics, systematic reporting, and an engineering mindset	41
The importance of microbiology reference laboratories and adequate funding for infectious disease surveillance	40
Harnessing wearables and mobile phones to improve glycemic outcomes with automated insulin delivery	40
Automated external defibrillator drones and their role in emergency response	40
AI for identification of systemic biomarkers from external eye photos: a promising field in the oculomics revolution	40
Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction model	40
Artificial intelligence in medicine and the pursuit of environmentally responsible science	39
Label-efficient computational tumour infiltrating lymphocyte assessment in breast cancer (ECTIL): multicentre validation in 2340 patients with breast cancer	39
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 hospitals	37
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility	37
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 trial	37
Utilising the Benefit Risk Assessment of Vaccines (BRAVE) toolkit to evaluate the benefits and risks of Vaxzevria in the EU: a population-based study	36
The potential for large language models to transform cardiovascular medicine	36
Reflecting on lived experience expertise in digital mental health research	36
A prospectively deployed deep learning-enabled automated quality assurance tool for oncological palliative spine radiation therapy	35
Effect of epileptic activity on outcome for critically ill patients	35
Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the FLARE22 challenge	35
Curbing the carbon footprint of health care	35
Wearable health data privacy	35
Artificial intelligence-driven cardiac amyloidosis screening	35
Importance of sample size on the quality and utility of AI-based prediction models for healthcare	35
Twitter, public health, and misinformation	34
Feedback loops in intensive care unit prognostic models: an under-recognised threat to clinical validity	34
The architectural gap in clinical artificial intelligence	34
Deep learning with weak annotation from diagnosis reports for detection of multiple head disorders: a prospective, multicentre study	33
Paediatric safety assessment of BNT162b2 vaccination in a multistate hospital-based electronic health record system in the USA: a retrospective analysis	33
Stepping stones and challenges in the use of artificial intelligence in the diagnosis of echinococcosis	33