Can Machine Learning Predict Alcohol Levels over the Legal Limit?
By Dr. Kirstin Aschbacher and colleagues.
Contributor
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
Increasing engagement with smartphone apps for anxiety and depression
Smartphone apps can reduce symptoms of depression and anxiety, but real-world users rarely use them for more than a few days. Our review aimed to identify features that make these apps more engaging and effective, which is especially crucial amidst the stress and isolation of the COVID-19 crisis.
COVID-19 was a Catalyst for Digital Health – Now, What Lies Ahead?
The COVID-19 pandemic has disrupted many industries, and healthcare is no exception. Digital health solutions deployed globally to facilitate extensive re-organisation of healthcare services and de-centralised care in the first 6 months of COVID-19 are presented with an overview of the road ahead.
