npj Digital Medicine

(The TQCC of npj Digital Medicine is 59. The table below lists those papers that are above that threshold based on CrossRef citation counts. The publications cover those that have been published in the past four years, i.e., from 2019-03-01 to 2023-03-01.)
The use of photoplethysmography for assessing hypertension246
Artificial intelligence and machine learning in clinical development: a translational perspective203
Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences193
Randomized controlled trial of a 12-week digital care program in improving low back pain190
Standalone smartphone apps for mental health—a systematic review and meta-analysis181
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization176
Wearable sensors for monitoring the physiological and biochemical profile of the athlete175
Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer172
Using science to sell apps: Evaluation of mental health app store quality claims163
Respiration rate and volume measurements using wearable strain sensors163
Digital biomarkers for Alzheimer’s disease: the mobile/wearable devices opportunity160
Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants158
Digital health: a path to validation154
The “inconvenient truth” about AI in healthcare146
Deep learning algorithm predicts diabetic retinopathy progression in individual patients134
Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety131
Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles124
Why digital medicine depends on interoperability123
Deep learning predicts hip fracture using confounding patient and healthcare variables115
Developing and adopting safe and effective digital biomarkers to improve patient outcomes111
Deep learning and alternative learning strategies for retrospective real-world clinical data109
By the numbers: ratings and utilization of behavioral health mobile applications106
Wearable sensors for monitoring the internal and external workload of the athlete99
Physician perspectives on integration of artificial intelligence into diagnostic pathology95
Patients’ views of wearable devices and AI in healthcare: findings from the ComPaRe e-cohort92
Best practices for analyzing large-scale health data from wearables and smartphone apps86
Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning85
Artificial intelligence for precision medicine in neurodevelopmental disorders81
Clinical assessment of a non-invasive wearable MEMS pressure sensor array for monitoring of arterial pulse waveform, heart rate and detection of atrial fibrillation81
Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program81
App-based multidisciplinary back pain treatment versus combined physiotherapy plus online education: a randomized controlled trial74
Similar image search for histopathology: SMILY65
Putting the data before the algorithm in big data addressing personalized healthcare63
Predicting scheduled hospital attendance with artificial intelligence60
Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care Unit60
The reproducibility crisis in the age of digital medicine59