Lancet Digital Health

Papers
(The H4-Index of Lancet Digital Health is 68. 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 2020-10-01 to 2024-10-01.)
ArticleCitations
The false hope of current approaches to explainable artificial intelligence in health care523
What social media told us in the time of COVID-19: a scoping review504
ChatGPT: the future of discharge summaries?390
Artificial intelligence in COVID-19 drug repurposing352
Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis342
Generating scholarly content with ChatGPT: ethical challenges for medical publishing299
Changes in the incidence of invasive disease due to Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis during the COVID-19 pandemic in 26 countries and territories in the Inv296
Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study240
Automated and partly automated contact tracing: a systematic review to inform the control of COVID-19235
Clinical features of COVID-19 mortality: development and validation of a clinical prediction model216
Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: a population-based study205
The online anti-vaccine movement in the age of COVID-19205
Using ChatGPT to write patient clinic letters197
Mask-wearing and control of SARS-CoV-2 transmission in the USA: a cross-sectional study195
AI recognition of patient race in medical imaging: a modelling study194
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability185
Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study164
Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses162
ChatGPT: friend or foe?161
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension155
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension152
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospect148
Predicting the risk of developing diabetic retinopathy using deep learning146
Health information technology and digital innovation for national learning health and care systems138
Health data poverty: an assailable barrier to equitable digital health care137
Time to reality check the promises of machine learning-powered precision medicine136
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study134
Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms130
Online health survey research during COVID-19128
Identifying who has long COVID in the USA: a machine learning approach using N3C data125
Ethics of large language models in medicine and medical research125
Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review122
Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study122
Interpreting area under the receiver operating characteristic curve119
Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study115
Heart rate variability with photoplethysmography in 8 million individuals: a cross-sectional study115
The medical algorithmic audit114
Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology108
Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review107
Characteristics of publicly available skin cancer image datasets: a systematic review105
Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs104
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study100
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study99
Association between digital smart device use and myopia: a systematic review and meta-analysis98
Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test95
Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study94
Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study94
Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms92
The effect of maternal SARS-CoV-2 infection timing on birth outcomes: a retrospective multicentre cohort study91
Blockchain applications in health care for COVID-19 and beyond: a systematic review89
Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study87
X-ray dark-field chest imaging for detection and quantification of emphysema in patients with chronic obstructive pulmonary disease: a diagnostic accuracy study86
The need for feminist intersectionality in digital health86
A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study86
Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study85
Explainability and artificial intelligence in medicine84
Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis83
Renin–angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis83
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study82
Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease82
Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study81
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis80
User characteristics and outcomes from a national digital mental health service: an observational study of registrants of the Australian MindSpot Clinic79
Mining whole-lung information by artificial intelligence for predicting EGFR genotype and targeted therapy response in lung cancer: a multicohort study75
Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study74
Advancing digital health applications: priorities for innovation in real-world evidence generation72
Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis71
From promise to practice: towards the realisation of AI-informed mental health care71
Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance68
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