Lancet Digital Health

(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 2020-04-01 to 2024-04-01.)
Applications of digital technology in COVID-19 pandemic planning and response596
What social media told us in the time of COVID-19: a scoping review446
The false hope of current approaches to explainable artificial intelligence in health care427
Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study341
Artificial intelligence in COVID-19 drug repurposing328
ChatGPT: the future of discharge summaries?286
Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis277
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 Inv257
COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread256
Automated and partly automated contact tracing: a systematic review to inform the control of COVID-19228
Generating scholarly content with ChatGPT: ethical challenges for medical publishing224
Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: a modelling study using mobile phone data219
Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study217
Building trust while influencing online COVID-19 content in the social media world214
The myth of generalisability in clinical research and machine learning in health care212
Clinical features of COVID-19 mortality: development and validation of a clinical prediction model207
Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid205
The online anti-vaccine movement in the age of COVID-19194
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 study193
Mask-wearing and control of SARS-CoV-2 transmission in the USA: a cross-sectional study188
Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records186
COVID-19 and the digital divide in the UK185
A novel digital intervention for actively reducing severity of paediatric ADHD (STARS-ADHD): a randomised controlled trial178
An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study166
A real-time dashboard of clinical trials for COVID-19164
Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study147
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability145
AI recognition of patient race in medical imaging: a modelling study142
Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study132
ChatGPT: friend or foe?131
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension131
Using ChatGPT to write patient clinic letters130
Predicting the risk of developing diabetic retinopathy using deep learning128
Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints128
A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations128
Time to reality check the promises of machine learning-powered precision medicine125
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 retrospect124
Clinical applications of continual learning machine learning122
Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study120
Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation118
Online health survey research during COVID-19117
Ethical limitations of algorithmic fairness solutions in health care machine learning115
Health data poverty: an assailable barrier to equitable digital health care113
Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms113
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension111
Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study111
Health information technology and digital innovation for national learning health and care systems106
The need for privacy with public digital contact tracing during the COVID-19 pandemic103
Identifying who has long COVID in the USA: a machine learning approach using N3C data102
Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses101
Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study100
Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology100
Heart rate variability with photoplethysmography in 8 million individuals: a cross-sectional study97
Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study95
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study91
Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review91
Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs90
Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test90
Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study89
The medical algorithmic audit86
Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study85
Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study85
Ethics of large language models in medicine and medical research81
Renin–angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis81
Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis81
The effect of maternal SARS-CoV-2 infection timing on birth outcomes: a retrospective multicentre cohort study81
Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms80
Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study78
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study78
Blockchain applications in health care for COVID-19 and beyond: a systematic review77
Characteristics of publicly available skin cancer image datasets: a systematic review77
Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study76
Sub-Saharan Africa—the new breeding ground for global digital health74
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 disease72
Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review71
X-ray dark-field chest imaging for detection and quantification of emphysema in patients with chronic obstructive pulmonary disease: a diagnostic accuracy study70
Interpreting area under the receiver operating characteristic curve69
Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study69
Association between digital smart device use and myopia: a systematic review and meta-analysis69
Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis68
User characteristics and outcomes from a national digital mental health service: an observational study of registrants of the Australian MindSpot Clinic68
A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study67
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis66
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study64
Virtual care: new models of caring for our patients and workforce64
Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation64
Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study63
Explainability and artificial intelligence in medicine63
The need for feminist intersectionality in digital health62
Effects of digital cognitive behavioural therapy for insomnia on insomnia severity: a large-scale randomised controlled trial60
Mining whole-lung information by artificial intelligence for predicting EGFR genotype and targeted therapy response in lung cancer: a multicohort study58
Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study58
A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study58
Advancing digital health applications: priorities for innovation in real-world evidence generation58
A simple nomogram for predicting failure of non-invasive respiratory strategies in adults with COVID-19: a retrospective multicentre study57
An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on bip55
Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database55
Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance55
Data sharing in the era of COVID-1954
Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study53
Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study52
Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT52
Ethical issues in using ambient intelligence in health-care settings51
The European artificial intelligence strategy: implications and challenges for digital health50
From promise to practice: towards the realisation of AI-informed mental health care50
Public perceptions on data sharing: key insights from the UK and the USA50
Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study49
Anosmia, ageusia, and other COVID-19-like symptoms in association with a positive SARS-CoV-2 test, across six national digital surveillance platforms: an observational study48
Machine learning for COVID-19—asking the right questions48
Addressing bias: artificial intelligence in cardiovascular medicine47
Effectiveness and safety of pulse oximetry in remote patient monitoring of patients with COVID-19: a systematic review46
Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study46
Improving epidemic surveillance and response: big data is dead, long live big data45
Performance of intensive care unit severity scoring systems across different ethnicities in the USA: a retrospective observational study44
The effects of physical distancing on population mobility during the COVID-19 pandemic in the UK44
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study43
Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data43
Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study42
Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis: a case-control development and validation study41
Deep learning-enabled pelvic ultrasound images for accurate diagnosis of ovarian cancer in China: a retrospective, multicentre, diagnostic study40
Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study40
Improving the health of young African American women in the preconception period using health information technology: a randomised controlled trial40
Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning stu40
Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicent39
Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation39
Continual learning in medical devices: FDA's action plan and beyond39
Observational study of UK mobile health apps for COVID-1938
Approaching autonomy in medical artificial intelligence38
Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge38
Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study38
Cautions about radiologic diagnosis of COVID-19 infection driven by artificial intelligence38
COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records38
Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study37
The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review37
WHO SMART guidelines: optimising country-level use of guideline recommendations in the digital age37
Dynamic prediction of psychological treatment outcomes: development and validation of a prediction model using routinely collected symptom data37
Crowdsourcing data to mitigate epidemics36
Africa turns to telemedicine to close mental health gap35
Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data35
COVID-19 detection from audio: seven grains of salt35
A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study35
Associations between changes in population mobility in response to the COVID-19 pandemic and socioeconomic factors at the city level in China and country level worldwide: a retrospective, observationa35
An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: a national validation cohort study in England33
Efficacy of telemedicine for the management of cardiovascular disease: a systematic review and meta-analysis33
Applications of predictive modelling early in the COVID-19 epidemic33
Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study33