Behind the paper
Share the real story behind your paper, from conception to publication, the highs and the lows.
The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing
Do seasonal variations in day length and temperature influence sleep in a world of climate control and electricity? Our study combined a year of wearable sleep data with meteorological data. We found that seasons, day length, and temperature influence when and how long individuals sleep.
Quantitative imaging in combination with clinical & lab data risk stratifies COVID19 patients
A case of multi-modal modeling of a complex disease using AI
Can Machine Learning Predict Alcohol Levels over the Legal Limit?
By Dr. Kirstin Aschbacher and colleagues.
Predicting severe COVID-19 using a simple clinical risk score
The combination of clinical and laboratory parameters on admission can accurately predict severe disease amongst COVID-19 patients
What is the diagnostic accuracy of deep learning algorithms on medical imaging and what is the quality of evidence supporting this?
Our systematic review and meta-analysis provides a critical assessment of the deep learning literature to date and proposes recommendations to improve the quality of deep learning research in the future.
Behind the paper: Machine Learning for Patient Risk Stratification: Standing on, or looking over, the shoulders of clinicians?
Our recent publication, Machine Learning for Patient Risk Stratification: Standing on, or looking over, the shoulders of clinicians?, in npj Digital Medicine examines the question of whether clinical machine learning models truly extend beyond what clinicians already suspect.
AI-based COVID-19 detection in chest CT, a privacy-preserving paradigm study
The COVID-19 pandemic has disrupted people daily life, digital health solutions empowered with AI could become critical and conducted in a safe way. To develop robust and reliable clinical tools capturing large variety and heterogeneity, a privacy-preserving learning strategy is worthwhile to study.
Can clinically validated digital therapeutics and rigorous clinical science address longstanding treatment challenges to improving outcomes for children with ADHD?
In spite of dozens of existing treatment options, children with Attention Deficit Hyperactivity Disorder (ADHD) still fare poorly across many domains. We explore a new frontier in which digital therapeutics could help address these challenges for ADHD specifically and mental health more broadly.
Wearable sensors can tell you more than just step count: measuring nighttime scratching and sleep
A more holistic picture of life with atopic dermatitis
