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 2022-01-01 to 2026-01-01.)

Article	Citations
Correction to Lancet Digit Health 2024; 6: e791–802	587
Accelerating action for gender equality in health	449
Retraction remedy: a resource for transparent science	395
In the era of digitalisation and biosignatures, is C-reactive protein still the one to beat?	357
Machine learning to predict type 1 diabetes in children	341
Balancing AI innovation with patient safety	331
A deep-learning-enabled diagnosis of ovarian cancer – Authors' reply	330
Correction to Lancet Digit Health 2023; 5: e446–57	261
Technology for world elimination of neglected tropical diseases	261
Targeting respiratory syncytial virus vaccination using individual prediction	235
Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study	225
Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world	216
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study	204
Challenges for augmenting intelligence in cardiac imaging	189
Embedding patient-reported outcomes at the heart of artificial intelligence health-care technologies	184
Generative Pre-trained Transformer 4 (GPT-4) in clinical settings	182
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis	181
Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models	178
ChatGPT: the future of discharge summaries?	174
AI-CAD for tuberculosis and other global high-burden diseases	172
A future role for health applications of large language models depends on regulators enforcing safety standards	167
Health insights from face photographs	166
Harnessing population-wide health data to predict cancer risk	164
Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis	159
Large language model integration in Philippine ophthalmology: early challenges and steps forward	147

Decolonising health data	140
Digital health funding for COVID-19 vaccine deployment across four major donor agencies	138
Building an evidence standards framework for artificial intelligence-enabled digital health technologies	136
Artificial intelligence deployment in diabetic retinopathy: the last step of the translation continuum	132
Efficacy of standalone smartphone apps for mental health: an updated systematic review and meta-analysis	130
Synthetic data, synthetic trust: navigating data challenges in the digital revolution	128
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	127
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	119
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study	119
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	118
Fairly evaluating the performance of normative models	111
Can electronic medical records predict neonatal seizures?	102
Thank you to The Lancet Digital Health's statistical and peer reviewers in 2022	101
Safe care from home for complicated pregnancies?	98
US COVID-19 clinical trial leadership gender disparities	97
Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study	96
Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study	96
Using artificial intelligence to switch from accident to sagacity in the serendipitous detection of uncommon diseases	95
An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation	93
A long STANDING commitment to improving health care	91
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	87
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations	87
The MAIDA initiative: establishing a framework for global medical-imaging data sharing	84
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study	83
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
Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study	78
Radiomics in neuro-oncological clinical trials	77
Overlooked and under-reported: the impact of cyberattacks on primary care in the UK National Health Service	76
A response to evaluating national data flows	76
Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study	74
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in England	73
Comprehensive genomic profiling and treatment patterns across ancestries in advanced prostate cancer: a large-scale retrospective analysis	72
Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study	72
Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis	68
A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan	68
Forging the tools for a computer-aided workflow in transplant pathology	66
Moving forward with machine learning models in acute chest pain	66
Pregnancy and SARS-CoV-2: an opportunity to systematically study the complexity of maternal health	66
Performance of universal and stratified computer-aided detection thresholds for chest x-ray-based tuberculosis screening: a cross-sectional, diagnostic accuracy study	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
Deep learning-enabled pelvic ultrasound images for accurate diagnosis of ovarian cancer in China: a retrospective, multicentre, diagnostic study	64