OOIR: Observatory of International Research

Papers

(The H4-Index of Lancet Digital Health is 64. 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.)

Article	Citations
Retraction remedy: a resource for transparent science	635
In the era of digitalisation and biosignatures, is C-reactive protein still the one to beat?	475
Correction to Lancet Digit Health 2023; 5: e446–57	474
Correction to Lancet Digit Health 2024; 6: e791–802	443
Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies	406
Accelerating action for gender equality in health	397
Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world	354
Machine learning to predict type 1 diabetes in children	296
Generative Pre-trained Transformer 4 (GPT-4) in clinical settings	255
Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models	255
Balancing AI innovation with patient safety	254
Technology for world elimination of neglected tropical diseases	225
Targeting respiratory syncytial virus vaccination using individual prediction	223
Challenges for augmenting intelligence in cardiac imaging	219
A deep-learning-enabled diagnosis of ovarian cancer – Authors' reply	215
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis	204
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study	201
Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study	197
ChatGPT: the future of discharge summaries?	158
Health insights from face photographs	153
Harnessing population-wide health data to predict cancer risk	150
Efficacy of standalone smartphone apps for mental health: an updated systematic review and meta-analysis	146
Fairly evaluating the performance of normative models	143
Synthetic data, synthetic trust: navigating data challenges in the digital revolution	138
Large language model integration in Philippine ophthalmology: early challenges and steps forward	133

Digital health funding for COVID-19 vaccine deployment across four major donor agencies	125
Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis	123
A future role for health applications of large language models depends on regulators enforcing safety standards	119
Decolonising health data	118
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	117
Bridging the gap: aligning clinical decision support regulation with clinical practice in the era of artificial intelligence	116
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	115
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	107
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study	101
Trust, not technology: governing access to health data as the decisive challenge for the UK	101
Thank you to The Lancet Digital Health's statistical and peer reviewers in 2022	100
AI-CAD for tuberculosis and other global high-burden diseases	100
Safe care from home for complicated pregnancies?	96
US COVID-19 clinical trial leadership gender disparities	94
Adolescent obesity in the digital age: navigating risks and opportunities	89
The MAIDA initiative: establishing a framework for global medical-imaging data sharing	87
Using artificial intelligence to switch from accident to sagacity in the serendipitous detection of uncommon diseases	86
Can electronic medical records predict neonatal seizures?	85
A long STANDING commitment to improving health care	85
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study	84
Interpreting the GRACE 3.0 ITE model: from predictive performance to clinical decision utility	83
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 trial	80
Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study	74
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	73
Radiomics in neuro-oncological clinical trials	73
A practical framework for operationalising responsible and equitable artificial intelligence in health care: tackling bias, inequity, and implementation challenges	72
Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study	72
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations	71
Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study	71
An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation	71
Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis	70
RareArena: a comprehensive benchmark dataset unveiling the potential of large language models in rare disease diagnosis	70
A response to evaluating national data flows	70
Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study	69
Overlooked and under-reported: the impact of cyberattacks on primary care in the UK National Health Service	69
AI-enabled forecasting of prehospital transfusion needs in patients with trauma: a multinational, registry-based, retrospective, machine learning development and validation study	68
Navigating the promise and pitfalls of dashboards in health policy decision making: experiences from Ghana, India, and South Africa	67
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in England	66
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	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
Co-intelligence: a proposal for human–artificial intelligence collaboration for large language models in medical research	64